Insights¶
This page outlines the operations, endpoints, parameters, and example requests and responses for the Insights.
DELETE /api/v2/dataSlices/¶
Data slices bulk deletion.
Code samples¶
# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/dataSlices/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{DataSlicesBulkDeleteRequest}'
Body parameter¶
{
"ids": [
"string"
]
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | DataSlicesBulkDeleteRequest | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
204 | No Content | The requested data slice(s) are deleted successfully. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/dataSlices/¶
Request to create a new data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/dataSlices/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{DataSlicesCreationRequest}'
Body parameter¶
{
"filters": [
{
"operand": "string",
"operator": "eq",
"values": [
"string"
]
}
],
"name": "string",
"projectId": "string"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | DataSlicesCreationRequest | false | none |
Example responses¶
200 Response
{
"filters": [
{
"operand": "string",
"operator": "eq",
"values": [
"string"
]
}
],
"id": "string",
"name": "string",
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | The requested data slice is created successfully. | DataSliceIndividualResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
DELETE /api/v2/dataSlices/{dataSliceId}/¶
Deletes the data slice specified by the data slice ID.
Code samples¶
# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/dataSlices/{dataSliceId}/ \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
dataSliceId | path | string | true | ID of the data slice. |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
204 | No Content | The specified data slice was deleted. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/dataSlices/{dataSliceId}/¶
Returns details about the specified data slice ID.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/dataSlices/{dataSliceId}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
dataSliceId | path | string | true | ID of the data slice. |
Example responses¶
200 Response
{
"filters": [
{
"operand": "string",
"operator": "eq",
"values": [
"string"
]
}
],
"id": "string",
"name": "string",
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Data slice was found. | DataSliceIndividualResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/dataSlices/{dataSliceId}/sliceSizes/¶
Returns the number of rows available after applying a data slice to the specified subset of the dataset.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/dataSlices/{dataSliceId}/sliceSizes/?projectId=string&source=backtest_0 \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | query | string | true | The project ID. |
source | query | string | true | The source of data to use to calculate the size. |
externalDatasetId | query | string | false | The external dataset ID to use when calculating the size of a slice. Use this parameter only when the source is 'externalTestSet'. |
modelId | query | string | false | The model ID whose training dataset should be sliced. Use this parameter only when the source is 'training'. |
dataSliceId | path | string | true | ID of the data slice. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , crossValidation , externalTestSet , holdout , holdout_training , training , validation ] |
Example responses¶
200 Response
{
"dataSliceId": "string",
"externalDatasetId": "string",
"messages": [
{
"additionalInfo": "string",
"description": "string",
"level": "CRITICAL"
}
],
"modelId": "string",
"projectId": "string",
"sliceSize": 0,
"source": "backtest_0"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | The subset slice size was retrieved. | DataSliceRetrieveSubsetSizeResponse |
204 | No Content | No slice size exists. | None |
403 | Forbidden | Unathorized access to resource. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/dataSlices/{dataSliceId}/sliceSizes/¶
Compute the number of rows available after applying a data slice to the specified subset of the dataset.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/dataSlices/{dataSliceId}/sliceSizes/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"externalDatasetId": "string",
"modelId": "string",
"projectId": "string",
"source": "backtest_0"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
dataSliceId | path | string | true | ID of the data slice. |
body | body | DataSliceComputeSubsetSizeRequest | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested data slices have been successfully validated. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/featureEffects/¶
Request calculation of Feature Effects with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/featureEffects/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeFeatureEffectsRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"source": "validation"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeFeatureEffectsRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested Feature Effect insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/featureEffects/models/{entityId}/¶
List of paginated Feature Effects insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/featureEffects/models/{entityId}/?limit=10&offset=0&source=validation \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | true | The subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
entityId | path | string | true | The ID of the model. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , training , backtest_0 , backtest_1 , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 , holdout , backtest_0_training , backtest_1_training , backtest_2_training , backtest_3_training , backtest_4_training , backtest_5_training , backtest_6_training , backtest_7_training , backtest_8_training , backtest_9_training , backtest_10_training , backtest_11_training , backtest_12_training , backtest_13_training , backtest_14_training , backtest_15_training , backtest_16_training , backtest_17_training , backtest_18_training , backtest_19_training , backtest_20_training , holdout_training ] |
unslicedOnly | [false , False , true , True ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"backtestIndex": "string",
"data": {
"featureEffects": [
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
]
},
"dataSliceId": "string",
"entityId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's Feature Effects, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | RetrieveFeatureEffectsPaginatedResponse |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/featureImpact/¶
Request calculation of insight with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/featureImpact/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeFeatureImpactRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"rowCount": 10,
"source": "training"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeFeatureImpactRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/featureImpact/models/{entityId}/¶
List of paginated Feature Impact insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/featureImpact/models/{entityId}/?limit=10&offset=0 \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | false | The subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
entityId | path | string | true | The ID of the model. |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , backtest_2_training , backtest_3_training , backtest_4_training , backtest_5_training , backtest_6_training , backtest_7_training , backtest_8_training , backtest_9_training , backtest_10_training , backtest_11_training , backtest_12_training , backtest_13_training , backtest_14_training , backtest_15_training , backtest_16_training , backtest_17_training , backtest_18_training , backtest_19_training , backtest_20_training , backtest_1_training , holdout_training ] |
unslicedOnly | [false , False , true , True ] |
Accept | application/json |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"data": {
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
],
"ranRedundancyDetection": true,
"rowCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"id": "string",
"projectId": "string",
"source": "training"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's Feature Impact, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | RetrieveFeatureImpactPaginatedResponse |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/liftChart/¶
Request calculation of insight with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/liftChart/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeLiftChartRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"source": "validation"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeLiftChartRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/liftChart/models/{entityId}/¶
List of paginated Lift chart insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/liftChart/models/{entityId}/?limit=10&offset=0 \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | false | The subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
externalDatasetId | query | string | false | The ID of the external dataset. |
entityId | path | string | true | The ID of the model. |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout , externalTestSet , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
unslicedOnly | [false , False , true , True ] |
Accept | application/json |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"data": {
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's Lift chart, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | RetrieveLiftChartPaginatedResponse |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/residuals/¶
Request calculation of insight with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/residuals/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeResidualsRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"source": "validation"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeResidualsRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/residuals/models/{entityId}/¶
List of paginated Residuals insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/residuals/models/{entityId}/?limit=10&offset=0 \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | false | The subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
externalDatasetId | query | string | false | The ID of the external dataset. |
entityId | path | string | true | The ID of the model. |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout , externalTestSet ] |
unslicedOnly | [false , False , true , True ] |
Accept | application/json |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"data": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's Residuals chart, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | RetrieveResidualsPaginatedResponse |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/rocCurve/¶
Request calculation of insight with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/rocCurve/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeRocCurveRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"source": "validation"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeRocCurveRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/rocCurve/models/{entityId}/¶
List of paginated ROC curve insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/rocCurve/models/{entityId}/?limit=10&offset=0 \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | false | The subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
externalDatasetId | query | string | false | The ID of the external dataset. |
entityId | path | string | true | The ID of the model. |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout , externalTestSet , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
unslicedOnly | [false , False , true , True ] |
Accept | application/json |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"data": {
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's ROC curve, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | RetrieveRocCurvePaginatedResponse |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/shapDistributions/¶
Request calculation of insight with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/shapDistributions/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeShapInsightsRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"quickCompute": true,
"rowCount": 0,
"source": "backtest_0"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeShapInsightsRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/shapDistributions/models/{entityId}/¶
List of paginated SHAP Distributions insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/shapDistributions/models/{entityId}/?limit=10&offset=0 \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | false | The subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
externalDatasetId | query | string | false | The ID of the external dataset. |
predictionFilterRowCount | query | integer | false | The maximum number of distribution rows to return. |
featureFilterCount | query | integer | false | The maximum number of features to return. |
featureFilterName | query | string | false | The names of the features to return. |
quickCompute | query | boolean | false | When enabled, the default, limits the rows used from the selected subset (training sample or slice). |
seriesId | query | string | false | The series ID used to filter records (for multiseries projects). |
forecastDistance | query | integer | false | The forecast distance used to retrieve insight data. |
featuresOrderBy | query | string | false | Order SHAP distributions by the specified field value. |
entityId | path | string | true | The ID of the model. |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , externalTestSet , holdout , holdout_training , training , validation ] |
unslicedOnly | [false , False , true , True ] |
featuresOrderBy | [featureImpact , -featureImpact , featureName , -featureName ] |
Accept | [application/json , text/csv ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"data": {
"features": [
{
"feature": "string",
"featureType": "T",
"impactNormalized": 1,
"impactUnnormalized": 0,
"shapValues": [
{
"featureRank": 0,
"featureValue": 0,
"predictionValue": 0,
"rowIndex": 0,
"shapValue": 0
}
]
}
],
"totalFeaturesCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's SHAP Distributions chart, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | string |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/shapImpact/¶
Request calculation of insight with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/shapImpact/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeShapInsightsRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"quickCompute": true,
"rowCount": 0,
"source": "backtest_0"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeShapInsightsRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/shapImpact/models/{entityId}/¶
List of paginated SHAP Impact insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/shapImpact/models/{entityId}/?limit=10&offset=0 \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | false | Subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
entityId | path | string | true | The ID of the model. |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [backtest_0 , backtest_0Training , backtest_1 , backtest_10 , backtest_10Training , backtest_11 , backtest_11Training , backtest_12 , backtest_12Training , backtest_13 , backtest_13Training , backtest_14 , backtest_14Training , backtest_15 , backtest_15Training , backtest_16 , backtest_16Training , backtest_17 , backtest_17Training , backtest_18 , backtest_18Training , backtest_19 , backtest_19Training , backtest_1Training , backtest_2 , backtest_20 , backtest_20Training , backtest_2Training , backtest_3 , backtest_3Training , backtest_4 , backtest_4Training , backtest_5 , backtest_5Training , backtest_6 , backtest_6Training , backtest_7 , backtest_7Training , backtest_8 , backtest_8Training , backtest_9 , backtest_9Training , externalTestSet , holdout , holdoutTraining , training , validation ] |
unslicedOnly | [false , False , true , True ] |
Accept | application/json |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"data": {
"baseValue": [
0
],
"link": "string",
"quickCompute": true,
"rowCount": 0,
"shapImpacts": [
{
"featureName": "string",
"impactNormalized": 0,
"impactUnnormalized": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's SHAP impact chart, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | RetrieveShapImpactPaginatedResponse |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/shapMatrix/¶
Request calculation of insight with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/shapMatrix/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeShapInsightsRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"quickCompute": true,
"rowCount": 0,
"source": "backtest_0"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeShapInsightsRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/shapMatrix/models/{entityId}/¶
List of paginated SHAP Matrix insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/shapMatrix/models/{entityId}/?limit=10&offset=0 \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | false | The subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
externalDatasetId | query | string | false | The ID of the external dataset. |
quickCompute | query | boolean | false | When enabled, limits the rows used from the selected source subset by default. When disabled, all rows are used. |
entityId | path | string | true | The ID of the model. |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , externalTestSet , holdout , holdout_training , training , validation ] |
unslicedOnly | [false , False , true , True ] |
Accept | application/json |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"data": {
"baseValue": [
0
],
"colnames": [
"string"
],
"linkFunction": "string",
"matrix": [
[
0
]
],
"rowIndex": [
0
],
"timeSeriesRowIndex": [
[
0
]
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's SHAP Matrix chart, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | RetrieveShapMatrixPaginatedResponse |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/insights/shapPreview/¶
Request calculation of insight with an optional data slice.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/insights/shapPreview/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{ComputeShapInsightsRequest}'
Body parameter¶
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"quickCompute": true,
"rowCount": 0,
"source": "backtest_0"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
body | body | ComputeShapInsightsRequest | false | none |
Example responses¶
202 Response
{
"qid": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The requested insights computation was accepted. | ComputeInsightsResponse |
422 | Unprocessable Entity | Unsupported project or model type, model not trained, or locked holdout. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/insights/shapPreview/models/{entityId}/¶
List of paginated SHAP Preview insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/insights/shapPreview/models/{entityId}/?limit=10&offset=0 \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
dataSliceId | query | string | false | ID of the data slice. |
source | query | string | false | The subset of data used to compute the insight. |
unslicedOnly | query | string | false | Return only insights without a data_slice_id. |
externalDatasetId | query | string | false | The ID of the external dataset. |
predictionFilterRowCount | query | integer | false | The maximum number of preview rows to return. |
predictionFilterPercentiles | query | integer | false | The number of percentile intervals to select from the total number of rows. This field will supersede predictionFilterRowCount if both are present. |
predictionFilterOperandFirst | query | number | false | The first operand to apply to filtered predictions. |
predictionFilterOperandSecond | query | number | false | The second operand to apply to filtered predictions. |
predictionFilterOperator | query | string | false | The operator to apply to filtered predictions. |
featureFilterCount | query | integer | false | The maximum number of features to return for each preview. |
featureFilterName | query | string | false | The names of specific features to return for each preview. |
quickCompute | query | boolean | false | When enabled, limits the rows used from the selected source subset by default. When disabled, all rows are used. |
seriesId | query | string | false | The series ID used to filter records (for multiseries projects). |
forecastDistance | query | integer | false | The forecast distance used to retrieve insight data. |
entityId | path | string | true | The ID of the model. |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , externalTestSet , holdout , holdout_training , training , validation ] |
unslicedOnly | [false , False , true , True ] |
predictionFilterOperator | [eq , in , < , > , between , notBetween ] |
Accept | [application/json , text/csv ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"data": {
"previews": [
{
"predictionValue": 0,
"previewValues": [
{
"featureName": "string",
"featureRank": 0,
"featureValue": "string",
"hasTextExplanations": true,
"isImage": true,
"shapValue": 0,
"textExplanations": [
"string"
]
}
],
"rowIndex": 0,
"totalPreviewFeatures": 0
}
],
"previewsCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieves a model's SHAP Preview chart, either for the specified data_slice_id or, if not specified, for all slices in the original data partition. | string |
404 | Not Found | Requested entity ID or data slice ID not found | None |
422 | Unprocessable Entity | Unsupported project type, or unsupported insight for model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
DELETE /api/v2/insights/{insightName}/models/{entityId}/¶
Delete insights for a specific model.
Code samples¶
# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/insights/{insightName}/models/{entityId}/ \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
insightName | path | string | true | The name of the insight to be deleted. |
entityId | path | string | true | The ID of the model. |
Enumerated Values¶
Parameter | Value |
---|---|
insightName | [clusteringBarycentersMetric , clusteringDTW , featureEffects , featureImpact , liftChart , residuals , rocCurve , segmentationPreview , shapDistributions , shapImpact , shapMatrix , shapPreview , silhouetteDTW , timeSeriesClusteringBarycenters ] |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
204 | No Content | Model insight records deleted. | None |
404 | Not Found | Data was not found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/multilabelInsights/{multilabelInsightsKey}/histogram/¶
Retrieve multicategorical feature histogram.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/multilabelInsights/{multilabelInsightsKey}/histogram/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
multilabelInsightsKey | path | string | true | Key for multilabel insights, unique per project, feature, and EDA stage. The most recent key can be retrieved via [GET /api/v2/projects/{projectId}/features/][get-apiv2projectsprojectidfeatures] or [GET /api/v2/projects/{projectId}/features/{featurename:featureName}/][get-apiv2projectsprojectidfeaturesfeaturenamefeaturename] |
Example responses¶
200 Response
{
"featureName": "string",
"histogram": [
{
"label": "string",
"plot": [
{
"labelRelevance": 1,
"rowCount": 0,
"rowPct": 100
},
{
"labelRelevance": 1,
"rowCount": 0,
"rowPct": 100
}
]
}
],
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Multicategorical feature histogram. | MulticategoricalHistogram |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseManualSelections/¶
Get all label lists.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseManualSelections/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
multilabelInsightsKey | path | string | true | Key for multilabel insights, unique per project, feature, and EDA stage. The most recent key can be retrieved via [GET /api/v2/projects/{projectId}/features/][get-apiv2projectsprojectidfeatures] or [GET /api/v2/projects/{projectId}/features/{featurename:featureName}/][get-apiv2projectsprojectidfeaturesfeaturenamefeaturename] |
Example responses¶
200 Response
{
"data": [
{
"columnLabels": [
"string"
],
"id": "string",
"name": "string",
"rowLabels": [
"string"
]
}
],
"featureName": "string",
"multilabelInsightsKey": "string",
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | All label lists | PairwiseManualSelectionsRetrieveResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseManualSelections/¶
Save a list of manually selected labels for Feature Statistics matrix.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseManualSelections/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"columnLabels": [
"string"
],
"featureName": "string",
"multilabelInsightsKey": "string",
"name": "string",
"projectId": "string",
"rowLabels": [
"string"
]
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
multilabelInsightsKey | path | string | true | Key for multilabel insights, unique per project, feature, and EDA stage. The most recent key can be retrieved via [GET /api/v2/projects/{projectId}/features/][get-apiv2projectsprojectidfeatures] or [GET /api/v2/projects/{projectId}/features/{featurename:featureName}/][get-apiv2projectsprojectidfeaturesfeaturenamefeaturename] |
body | body | PairwiseManualSelectionCreatePayload | false | none |
Example responses¶
200 Response
{
"id": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Whether manually selected labels were saved successfully. | PairwiseManualSelectionCreateResponse |
422 | Unprocessable Entity | The manual selection name is already taken or another exception occurred. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
DELETE /api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseManualSelections/{manualSelectionListId}/¶
Delete label list.
Code samples¶
# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseManualSelections/{manualSelectionListId}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
multilabelInsightsKey | path | string | true | Key for multilabel insights, unique per project, feature, and EDA stage. The most recent key can be retrieved via [GET /api/v2/projects/{projectId}/features/][get-apiv2projectsprojectidfeatures] or [GET /api/v2/projects/{projectId}/features/{featurename:featureName}/][get-apiv2projectsprojectidfeaturesfeaturenamefeaturename] |
manualSelectionListId | path | string | true | ID of the label set. |
Example responses¶
200 Response
{
"manualSelectionId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | ID of the deleted label list. | PairwiseManualSelectionResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
PATCH /api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseManualSelections/{manualSelectionListId}/¶
Update label list's name.
Code samples¶
# You can also use wget
curl -X PATCH https://app.datarobot.com/api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseManualSelections/{manualSelectionListId}/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"name": "string"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
multilabelInsightsKey | path | string | true | Key for multilabel insights, unique per project, feature, and EDA stage. The most recent key can be retrieved via [GET /api/v2/projects/{projectId}/features/][get-apiv2projectsprojectidfeatures] or [GET /api/v2/projects/{projectId}/features/{featurename:featureName}/][get-apiv2projectsprojectidfeaturesfeaturenamefeaturename] |
manualSelectionListId | path | string | true | ID of the label set. |
body | body | PairwiseManualSelectionUpdateRequest | false | none |
Example responses¶
200 Response
{
"manualSelectionId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | ID of the updated label list. | PairwiseManualSelectionResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseStatistics/¶
Retrieve multilabel specific pairwise label statistics for the given multilabel insights key: correlation, joint probability and conditional probability.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/multilabelInsights/{multilabelInsightsKey}/pairwiseStatistics/?statisticType=conditionalProbability \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
statisticType | query | string | true | Type of pairwise statistic. |
multilabelInsightsKey | path | string | true | Key for multilabel insights, unique per project, feature, and EDA stage. The most recent key can be retrieved via [GET /api/v2/projects/{projectId}/features/][get-apiv2projectsprojectidfeatures] or [GET /api/v2/projects/{projectId}/features/{featurename:featureName}/][get-apiv2projectsprojectidfeaturesfeaturenamefeaturename] |
Enumerated Values¶
Parameter | Value |
---|---|
statisticType | [conditionalProbability , correlation , jointProbability ] |
Example responses¶
200 Response
{
"data": [
{
"labelConfiguration": [
{
"label": "string",
"relevance": 1
},
{
"label": "string",
"relevance": 1
}
],
"statisticValue": 0
}
],
"featureName": "string",
"projectId": "stringstringstringstring",
"statisticType": "conditionalProbability"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Pairwise label statistics. | PairwiseStatisticsResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/anomalyAssessmentRecords/¶
Retrieve anomaly assessment records.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/anomalyAssessmentRecords/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
modelId | query | string | false | The model ID to filter records by. |
backtest | query | any | false | The backtest to filter records by. |
source | query | string | false | The source of the data to filter records by. |
seriesId | query | string | false | Can be specified for multiseries projects. The series id to filter records by. |
projectId | path | string | true | The project ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"backtest": 19,
"deleteLocation": "http://example.com",
"endDate": "2019-08-24T14:15:22Z",
"latestExplanationsLocation": "http://example.com",
"modelId": "string",
"predictionThreshold": 0,
"previewLocation": "http://example.com",
"projectId": "string",
"recordId": "string",
"seriesId": "string",
"source": "training",
"startDate": "2019-08-24T14:15:22Z",
"status": "noData",
"statusDetails": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve anomaly assessment records. | AnomalyAssessmentRecordsResponse |
404 | Not Found | No data found | None |
422 | Unprocessable Entity | Input parameters are invalid | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
DELETE /api/v2/projects/{projectId}/anomalyAssessmentRecords/{recordId}/¶
Delete the anomaly assessment record.
Code samples¶
# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/projects/{projectId}/anomalyAssessmentRecords/{recordId}/ \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
recordId | path | string | true | The anomaly assessment record ID |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
204 | No Content | Anomaly assessment record deleted. | None |
404 | Not Found | Data was not found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/anomalyAssessmentRecords/{recordId}/explanations/¶
Retrieve anomaly assessment record.
Two out of three parameters: startDate
, endDate
or pointsCount
must be specified.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/anomalyAssessmentRecords/{recordId}/explanations/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
startDate | query | string(date-time) | false | The start of the date range to return. Date should be in UTC format. For example: 2019-08-01T00:00:00.000000Z . |
endDate | query | string(date-time) | false | The end of the date range to return, inclusive. Date should be in UTC format. For example: 2020-01-01T00:00:00.000000Z . |
pointsCount | query | integer | false | Count of points to return. |
projectId | path | string | true | The project ID |
recordId | path | string | true | The anomaly assessment record ID |
Example responses¶
200 Response
{
"backtest": 19,
"count": 0,
"data": [
{
"prediction": 0,
"shapExplanation": [
{
"feature": "string",
"featureValue": "string",
"strength": 0
}
],
"timestamp": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"modelId": "string",
"projectId": "string",
"recordId": "string",
"seriesId": "string",
"shapBaseValue": 0,
"source": "training",
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Anomaly assessment record. | AnomalyAssessmentExplanationsResponse |
404 | Not Found | Data was not found. | None |
422 | Unprocessable Entity | Insight is not available. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/anomalyAssessmentRecords/{recordId}/predictionsPreview/¶
Retrieve predictions preview for the anomaly assessment record.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/anomalyAssessmentRecords/{recordId}/predictionsPreview/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
recordId | path | string | true | The anomaly assessment record ID |
Example responses¶
200 Response
{
"backtest": 19,
"endDate": "2019-08-24T14:15:22Z",
"modelId": "string",
"previewBins": [
{
"avgPredicted": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"maxPredicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"projectId": "string",
"recordId": "string",
"seriesId": "string",
"source": "training",
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Predictions preview for the anomaly assessment record. | AnomalyAssessmentPreviewResponse |
404 | Not Found | Record not found. | None |
422 | Unprocessable Entity | Predictions preview is not available. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/biasVsAccuracyInsights/¶
Retrieve a list of Bias vs Accuracy insights for the model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/biasVsAccuracyInsights/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
accuracyMetric | query | string | false | The metric to return model accuracy scores. Defaults to the optimization metric configured in project options. |
protectedFeature | query | any | false | Name of the protected feature. |
fairnessMetric | query | any | false | The fairness metric used to calculate the fairness scores. |
projectId | path | string | true | The project ID |
Enumerated Values¶
Parameter | Value |
---|---|
accuracyMetric | [AUC , Weighted AUC , Area Under PR Curve , Weighted Area Under PR Curve , Kolmogorov-Smirnov , Weighted Kolmogorov-Smirnov , FVE Binomial , Weighted FVE Binomial , Gini Norm , Weighted Gini Norm , LogLoss , Weighted LogLoss , Max MCC , Weighted Max MCC , Rate@Top5% , Weighted Rate@Top5% , Rate@Top10% , Weighted Rate@Top10% , Rate@TopTenth% , RMSE , Weighted RMSE ] |
Example responses¶
200 Response
{
"data": [
{
"accuracyMetric": "AUC",
"fairnessMetric": "proportionalParity",
"fairnessThreshold": 0.8,
"models": [
{
"accuracyValue": 0,
"bp": 0,
"dsName": "string",
"fairnessValue": 1,
"modelId": "string",
"modelNumber": 0,
"modelType": "string",
"prime": true,
"samplepct": 100
}
],
"protectedFeature": "string"
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Returns Bias vs Accuracy results. | BiasVsAccuracyInsightRetrieve |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/dataSlices/¶
Returns a paginated list of data slices for the given project ID.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/dataSlices/?limit=100&offset=0 \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
limit | query | integer | true | The numbers of items to return. |
offset | query | integer | true | The number of items to skip before starting to collect the result set. |
projectId | path | string | true | The project ID. |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"filters": [
{
"operand": "string",
"operator": "eq",
"values": [
"string"
]
}
],
"id": "string",
"name": "string",
"projectId": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | List of data slices for the project was successfully retrieved. | DataSlicesListAllSlicesResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/accuracyOverTimePlots/¶
Retrieve the data for the Accuracy over Time plots.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/accuracyOverTimePlots/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided an average plot for the first 1000 series will be retrieved. |
backtest | query | any | false | Retrieve plots for a specific backtest (use the backtest index starting from zero) or holdout . If not specified the first backtest (backtest index 0) will be used. |
source | query | string | false | The source of the data for the backtest/holdout. |
forecastDistance | query | integer | false | Forecast distance to retrieve the data for. If not specified, the first forecast distance for this project will be used. Forecast distance specifies the number of time steps between the predicted point and the origin point. Only available for time series supervised projects. |
resolution | query | string | false | Specifying at which resolution the data should be binned. If not specified, optimal resolution will be used to build chart data with number of bins <= maxBinSize |
maxBinSize | query | integer | false | Specifies the maximum number of bins for the retrieval. |
startDate | query | string(date-time) | false | The start of the date range to return. If not specified, start date for requested plots will be used. |
endDate | query | string(date-time) | false | The end of the date range to return. If not specified, end date for requested plots will be used. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation ] |
resolution | [milliseconds , seconds , minutes , hours , days , weeks , months , quarters , years ] |
Example responses¶
200 Response
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"calendarEvents": [
{
"date": "2019-08-24T14:15:22Z",
"name": "string",
"seriesId": "string"
}
],
"endDate": "2019-08-24T14:15:22Z",
"resolution": "milliseconds",
"startDate": "2019-08-24T14:15:22Z",
"statistics": {
"durbinWatson": 4
}
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Accuracy over Time plots data | AccuracyOverTimePlotsDataResponse |
404 | Not Found | Accuracy over Time plots data was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/accuracyOverTimePlots/metadata/¶
Retrieve the metadata for the Accuracy over Time insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/accuracyOverTimePlots/metadata/ \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
forecastDistance | query | integer | false | Forecast distance to retrieve the data for. If not specified, the first forecast distance for this project will be used. Forecast distance specifies the number of time steps between the predicted point and the origin point. Only available for time series supervised projects. |
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided a metadata of average plot for the first 1000 series will be retrieved. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
Accept | application/json |
Example responses¶
200 Response
{
"backtestMetadata": [
{
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
}
],
"backtestStatuses": [
{
"training": "completed",
"validation": "completed"
}
],
"estimatedSeriesLimit": 1,
"forecastDistance": 1000,
"holdoutMetadata": {
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
},
"holdoutStatuses": {
"training": "completed",
"validation": "completed"
},
"resolutions": [
"milliseconds"
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Accuracy over Time insight metadata | AccuracyOverTimePlotsMetadataResponse |
404 | Not Found | Accuracy over Time insight metadata was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/accuracyOverTimePlots/preview/¶
Retrieve the preview for the Accuracy over Time plots.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/accuracyOverTimePlots/preview/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided an average plot for the first 1000 series will be retrieved. |
backtest | query | any | false | Retrieve plots for a specific backtest (use the backtest index starting from zero) or holdout . If not specified the first backtest (backtest index 0) will be used. |
source | query | string | false | The source of the data for the backtest/holdout. |
forecastDistance | query | integer | false | Forecast distance to retrieve the data for. If not specified, the first forecast distance for this project will be used. Forecast distance specifies the number of time steps between the predicted point and the origin point. Only available for time series supervised projects. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation ] |
Example responses¶
200 Response
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Accuracy over Time plots preview | DatetimeTrendPlotsPreviewResponse |
404 | Not Found | Accuracy over Time plots preview was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/anomalyOverTimePlots/¶
Retrieve the data for the Anomaly over Time plots.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/anomalyOverTimePlots/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided an average plot for the first 1000 series will be retrieved. |
backtest | query | any | false | Retrieve plots for a specific backtest (use the backtest index starting from zero) or holdout . If not specified the first backtest (backtest index 0) will be used. |
source | query | string | false | The source of the data for the backtest/holdout. |
resolution | query | string | false | Specifying at which resolution the data should be binned. If not specified, optimal resolution will be used to build chart data with number of bins <= maxBinSize |
maxBinSize | query | integer | false | Specifies the maximum number of bins for the retrieval. |
startDate | query | string(date-time) | false | The start of the date range to return. If not specified, start date for requested plots will be used. |
endDate | query | string(date-time) | false | The end of the date range to return. If not specified, end date for requested plots will be used. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation ] |
resolution | [milliseconds , seconds , minutes , hours , days , weeks , months , quarters , years ] |
Example responses¶
200 Response
{
"bins": [
{
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"calendarEvents": [
{
"date": "2019-08-24T14:15:22Z",
"name": "string",
"seriesId": "string"
}
],
"endDate": "2019-08-24T14:15:22Z",
"resolution": "milliseconds",
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Anomaly over Time plots data | AnomalyOverTimePlotsDataResponse |
404 | Not Found | Anomaly over Time plots data was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/anomalyOverTimePlots/metadata/¶
Retrieve the metadata for the Anomaly over Time insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/anomalyOverTimePlots/metadata/ \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided a metadata of average plot for the first 1000 series will be retrieved. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
Accept | application/json |
Example responses¶
200 Response
{
"backtestMetadata": [
{
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
}
],
"backtestStatuses": [
{
"training": "completed",
"validation": "completed"
}
],
"estimatedSeriesLimit": 1,
"holdoutMetadata": {
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
},
"holdoutStatuses": {
"training": "completed",
"validation": "completed"
},
"resolutions": [
"milliseconds"
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Anomaly over Time insights metadata | AnomalyOverTimePlotsMetadataResponse |
404 | Not Found | Anomaly over Time insights metadata was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/anomalyOverTimePlots/preview/¶
Retrieve the preview for the Anomaly over Time plots.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/anomalyOverTimePlots/preview/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided an average plot for the first 1000 series will be retrieved. |
backtest | query | any | false | Retrieve plots for a specific backtest (use the backtest index starting from zero) or holdout . If not specified the first backtest (backtest index 0) will be used. |
source | query | string | false | The source of the data for the backtest/holdout. |
predictionThreshold | query | number | false | Only bins with predictions exceeding this threshold will be returned in the response. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation ] |
Example responses¶
200 Response
{
"bins": [
{
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"predictionThreshold": 0,
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Anomaly over Time plots preview | AnomalyOverTimePlotsPreviewResponse |
404 | Not Found | Anomaly over Time plots preview was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/backtestStabilityPlot/¶
Retrieve a plot displaying the stability of the datetime model across different backtests.
All durations and datetimes should be specified in accordance with the :ref:timestamp and duration formatting rules<time_format>
.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/backtestStabilityPlot/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
metricName | query | string | false | The name of the metric to retrieve the scores for. If omitted, the default project metric will be used |
forecastDistance | query | integer | false | The forecast distance to retrieve the plot for. If not specified, the scores for each partition are aggregated across all forecast distances. This parameter is only available for time series models. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"backtestPlotData": [
{
"backtestIndex": 0,
"partition": "string",
"score": 0,
"scoringEndDate": "2019-08-24T14:15:22Z",
"scoringStartDate": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"metricName": "string",
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Backtest stability plot data for datetime partitioned model. | BacktestStabilityPlotResponse |
422 | Unprocessable Entity | Backtest stability plot data not available. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/datasetAccuracyOverTimePlots/{datasetId}/¶
Retrieve the Accuracy Over Time (AOT) chart data for an external dataset for a project.
Datetimes are specified in accordance with :ref:timestamp and duration formatting rules <time_format>
.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/datasetAccuracyOverTimePlots/{datasetId}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
maxBinSize | query | integer | false | The limit of returned bins. |
startDate | query | string(date-time) | false | The start of the date range to return (UTC string), for example: '2010-05-13T00:00:00.000000Z'. If not specified, the start date for this model and source of the data will be used instead. |
endDate | query | string(date-time) | false | The end of the date range to return (UTC string), for example: '2010-05-13T00:00:00.000000Z'. If not specified, the end date for this model and source of the data will be used instead. |
resolution | query | string | false | Specifies at which resolution the data should be binned. If not specified, optimal resolution will be used to build chart data such that bins <= maxBinSize . |
projectId | path | string | true | The project id which was used to compute the AOT chart. |
modelId | path | string | true | The model id which was used to compute the AOT chart. |
datasetId | path | string | true | The dataset id which was used to compute the AOT chart. |
Enumerated Values¶
Parameter | Value |
---|---|
resolution | [microseconds , milliseconds , seconds , minutes , hours , days , weeks , months , quarters , years ] |
Example responses¶
200 Response
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"datasetId": "string",
"endDate": "2019-08-24T14:15:22Z",
"modelId": "string",
"projectId": "string",
"resolution": "microseconds",
"startDate": "2019-08-24T14:15:22Z",
"statistics": {
"durbinWatson": 0
}
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Accuracy Over Time (AOT) chart data for an external dataset for a project. | AOTChartRetrieveResponse |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/datasetAccuracyOverTimePlots/{datasetId}/metadata/¶
Retrieve the metadata of the Accuracy Over Time (AOT) chart for an external dataset.
Datetimes are specified in accordance with :ref:timestamp and duration formatting rules <time_format>
.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/datasetAccuracyOverTimePlots/{datasetId}/metadata/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project id which was used to compute the AOT chart. |
modelId | path | string | true | The model id which was used to compute the AOT chart. |
datasetId | path | string | true | The dataset id which was used to compute the AOT chart. |
Example responses¶
200 Response
{
"datasetId": "string",
"datasetMetadata": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"frequencyType": "rowCount",
"metricName": "string",
"modelId": "string",
"projectId": "string",
"resolutions": [
"microseconds"
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Metadata of the Accuracy Over Time (AOT) chart for an external dataset. | AOTChartMetadataResponse |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/datasetAccuracyOverTimePlots/{datasetId}/preview/¶
Retrieve a preview of the Accuracy Over Time (AOT) chart for an external dataset.
Datetimes are specified in accordance with :ref:timestamp and duration formatting rules <time_format>
.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/datasetAccuracyOverTimePlots/{datasetId}/preview/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project id which was used to compute the AOT chart. |
modelId | path | string | true | The model id which was used to compute the AOT chart. |
datasetId | path | string | true | The dataset id which was used to compute the AOT chart. |
Example responses¶
200 Response
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"datasetId": "string",
"modelId": "string",
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Preview of the Accuracy Over Time (AOT) chart for an external dataset. | AOTChartPreviewResponse |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/datetimeModels/{modelId}/datetimeTrendPlots/¶
Computes Datetime Trend plots for time series and OTV projects: * For OTV projects, computes Accuracy over Time plots. * For time series supervised projects, computes both Accuracy over Time plots and Forecast vs Actual plots. .. minversion:: v2.25 * For unsupervised time series and OTV models, computes Anomaly Over Time plots. .. note:: For the multiseries time series projects only first 1000 series in alphabetical order and an average plot for them will be computed. .. note:: Maximum 100 forecast distances can be requested for calculation in time series supervised projects.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/datetimeTrendPlots/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"backtest": 0,
"forecastDistanceEnd": 0,
"forecastDistanceStart": 0,
"fullAverage": false,
"seriesIds": [
"string"
],
"source": "training"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | DatetimeTrendPlotsCreate | false | none |
Example responses¶
202 Response
{
"message": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | Datetime Trend plots computation job submitted successfully. | DatetimeTrendPlotsResponse |
422 | Unprocessable Entity | There were invalid parameters in the submitted request. See the message field for more details. |
None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/featureEffects/¶
Retrieve Feature Effects for a model backtest.
Feature Effects provides partial dependence and predicted vs actual values for the top 500 features, ordered by feature impact score.
The partial dependence shows marginal effect of a feature on the target variable after accounting for the average effects of all other predictive features. It indicates how, holding all other variables except the feature of interest as they were, the value of this feature affects your prediction.
If a Feature Effects job was previously submitted for a given backtest, this endpoint will return a response structured as {"message": jobId
is the ID of the job. Retrieve the job with GET /api/v2/projects/{projectId}/jobs/{jobId}/
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/featureEffects/?backtestIndex=string \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
source | query | string | false | Models data source. |
backtestIndex | query | string | true | The backtest index. For example: 0 , 1 , ..., 20 , holdout , startstop . |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation , holdout ] |
Example responses¶
200 Response
{
"backtestIndex": "string",
"featureEffects": [
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
],
"modelId": "string",
"projectId": "string",
"source": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | FeatureEffectsDatetimeResponse |
403 | Forbidden | User does not have permission to view the project. | None |
404 | Not Found | Project, model, source, backtest index, or computation results do not exist. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/datetimeModels/{modelId}/featureEffects/¶
Add a request to the queue to calculate Feature Effects for a backtest.
If the job has been previously submitted, the request fails, returning the jobId
of the previously submitted job. Use this jobId
to check status of the previously submitted job.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/featureEffects/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"backtestIndex": "string",
"rowCount": 10
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | FeatureEffectsCreateDatetime | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The Feature Effects request for a backtest has been successfully submitted. See Location header. | None |
403 | Forbidden | User does not have permission to view or submit jobs for the project. | None |
404 | Not Found | Provided project, model, or backtest index does not exist. | None |
422 | Unprocessable Entity | Queue submission error. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/featureEffectsMetadata/¶
Retrieve Feature Effects metadata for each backtest. Response contains status and available sources for each backtest of the model.
One of the provided backtestIndex
indexes used for submitting the compute request and retrieving Feature Effects.
* Start/stop models contain a single backtestIndex
response value of startstop
.
* Other models contain backtestIndex
of 0
, 1
, ..., holdout
.
One of the provided source
parameters used for retrieving Feature Effects.
* Each backtest source can be, at a minimum, training
or validation
. If holdout is configured for the project, backtestIndex
also includes holdout
with sources training
and holdout
.
* Source value of training
is always available. (versions prior to v2.17 support validation
only)
* When a start/stop model is trained into validation
or holdout
without stacked predictions (i.e., no out-of-sample predictions in validation
or holdout
), validation
and holdout
sources are not available.
* Source holdout
is not available when there is no holdout configured for the project.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/featureEffectsMetadata/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"data": [
{
"backtestIndex": "string",
"sources": [
"training"
],
"status": "INPROGRESS"
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | ModelXrayMetadataDatetimeResponse |
403 | Forbidden | User does not have permission to view the project. | None |
404 | Not Found | Project or model does not exist. | None |
422 | Unprocessable Entity | The model is not datetime partitioned. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/forecastDistanceStabilityPlot/¶
Retrieve a plot displaying the stability of the time series model across different forecast distances.
.. note::
All durations and datetimes are specified in accordance with the :ref:timestamp and duration formatting rules <time_format>
.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/forecastDistanceStabilityPlot/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
metricName | query | string | false | The name of the metric to retrieve the scores for. If omitted, the default project metric will be used. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"endDate": "2019-08-24T14:15:22Z",
"forecastDistancePlotData": [
{
"backtestingScore": 0,
"forecastDistance": 0,
"holdoutScore": 0,
"validationScore": 0
}
],
"metricName": "string",
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Forecast distance stability plot for datetime partitioned model. | ForecastDistanceStabilityPlotResponse |
422 | Unprocessable Entity | There was an error while retrieving the plot. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/forecastVsActualPlots/¶
Retrieve the data for the Forecast vs Actual plots.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/forecastVsActualPlots/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided an average plot for the first 1000 series will be retrieved. |
backtest | query | any | false | Retrieve plots for a specific backtest (use the backtest index starting from zero) or holdout . If not specified the first backtest (backtest index 0) will be used. |
source | query | string | false | The source of the data for the backtest/holdout. |
resolution | query | string | false | Specifying at which resolution the data should be binned. If not specified, optimal resolution will be used to build chart data with number of bins <= maxBinSize |
forecastDistanceStart | query | integer | false | The start of forecast distance range (forecast window) to retrieve. If not specified, the first forecast distance for this project will be used. Forecast distance specifies the number of time steps between the predicted point and the origin point. Only available for time series supervised projects. |
forecastDistanceEnd | query | integer | false | The end of forecast distance range (forecast window) to retrieve. If not specified, the last forecast distance for this project will be used. Forecast distance specifies the number of time steps between the predicted point and the origin point. Only available for time series supervised projects. |
maxBinSize | query | integer | false | Specifies the maximum number of bins for the retrieval. |
startDate | query | string(date-time) | false | The start of the date range to return. If not specified, start date for requested plots will be used. |
endDate | query | string(date-time) | false | The end of the date range to return. If not specified, end date for requested plots will be used. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation ] |
resolution | [milliseconds , seconds , minutes , hours , days , weeks , months , quarters , years ] |
Example responses¶
200 Response
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"error": 0,
"forecasts": [
0
],
"frequency": 0,
"normalizedError": 1,
"startDate": "2019-08-24T14:15:22Z"
}
],
"calendarEvents": [
{
"date": "2019-08-24T14:15:22Z",
"name": "string",
"seriesId": "string"
}
],
"endDate": "2019-08-24T14:15:22Z",
"forecastDistances": [
1
],
"resolution": "milliseconds",
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Forecast vs Actual plots data | ForecastVsActualPlotsDataResponse |
404 | Not Found | Forecast vs Actual plots data was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/forecastVsActualPlots/metadata/¶
Retrieve the metadata for the Forecast vs Actual insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/forecastVsActualPlots/metadata/ \
-H "Accept: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided a metadata of average plot for the first 1000 series will be retrieved. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Accept | header | string | false | Requested MIME type for the returned data. |
Enumerated Values¶
Parameter | Value |
---|---|
Accept | application/json |
Example responses¶
200 Response
{
"backtestMetadata": [
{
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
}
],
"backtestStatuses": [
{
"training": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
},
"validation": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
}
}
],
"estimatedSeriesLimit": 1,
"holdoutMetadata": {
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
},
"holdoutStatuses": {
"training": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
},
"validation": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
}
},
"resolutions": [
"milliseconds"
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Forecast vs Actual insights metadata | ForecastVsActualPlotsMetadataResponse |
404 | Not Found | Forecast vs Actual insights metadata was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/forecastVsActualPlots/preview/¶
Retrieve the preview for the Forecast vs Actual plots.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/forecastVsActualPlots/preview/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
seriesId | query | string | false | The name of the series to retrieve. Only available for time series multiseries projects. If not provided an average plot for the first 1000 series will be retrieved. |
backtest | query | any | false | Retrieve plots for a specific backtest (use the backtest index starting from zero) or holdout . If not specified the first backtest (backtest index 0) will be used. |
source | query | string | false | The source of the data for the backtest/holdout. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation ] |
Example responses¶
200 Response
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Forecast vs Actual plots preview | DatetimeTrendPlotsPreviewResponse |
404 | Not Found | Forecast vs Actual plots preview was not found | None |
422 | Unprocessable Entity | Invalid parameters were submitted | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/multiclassFeatureEffects/¶
Retrieve feature effects for each class in a multiclass datetime model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/multiclassFeatureEffects/?backtestIndex=string \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
source | query | string | false | Models data source. |
backtestIndex | query | string | true | The backtest index. For example: 0 , 1 , ..., 20 , holdout , startstop . |
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
class | query | string | false | Target class label. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation , holdout ] |
Example responses¶
200 Response
{
"backtestIndex": "string",
"count": 0,
"data": [
{
"class": "string",
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
],
"modelId": "string",
"next": "http://example.com",
"previous": "http://example.com",
"projectId": "string",
"source": "string",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | MulticlassDatetimeFeatureEffectsResponse |
403 | Forbidden | User does not have permission to view the project. | None |
404 | Not Found | Project, model, source or computation results do not exist. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/datetimeModels/{modelId}/multiclassFeatureEffects/¶
Compute feature effects for a multiclass datetime model. If the job has been previously submitted, the request fails, returning the jobId
of the previously submitted job. Use this jobId
to check status of the previously submitted job.
NOTE: feature effects are computed for top 100 classes.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/multiclassFeatureEffects/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"backtestIndex": "string",
"features": [
"string"
],
"rowCount": 10,
"topNFeatures": 0
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | MulticlassFeatureEffectDatetimeCreate | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The Feature Effects request has been successfully submitted. See Location header. | None |
403 | Forbidden | User does not have permission to view or submit jobs for the project. | None |
404 | Not Found | Project, model, source or computation results do not exist. | None |
422 | Unprocessable Entity | Queue submission error. If the rowCount exceeds the maximum or minimum value for this dataset. Minimum is 10 rows. Maximum is 100000 rows or the training sample size of the model, whichever is less. If invalid class names are provided in classes .If neither features nor topNFeatures is provided. If invalid backtestIndex is provided. |
None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/multiseriesHistograms/¶
Retrieve the histograms for series insights.
Histogram is computed only for first 1000 series (ordered by name).
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/multiseriesHistograms/?attribute=rowCount&bins=10 \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
attribute | query | string | true | The series attribute to build a histogram for. |
metric | query | string | false | The name of the metric to retrieve the histogram for attributes "validationScore", "backtestingScore", and"holdoutScore". If omitted, the default project metric will be used. |
bins | query | string | true | The number of bins in a histogram. Can be 10, 20 or 50. The default is 10. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
attribute | [rowCount , duration , startDate , endDate , targetAverage , validationScore , backtestingScore , holdoutScore , rowPercent , clusterCount , clustering ] |
bins | [10 , 20 , 50 ] |
Example responses¶
200 Response
{
"bins": [
{
"count": 0,
"left": 0,
"right": 0
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve the histograms for series insights in form of an array of histogram bins. | MultiseriesHistogramsRetrieveResponse |
403 | Forbidden | User does not have permissions to manage models. | None |
404 | Not Found | Model with specified modelId doesn't exist, or user does not have access to the project. |
None |
422 | Unprocessable Entity | Metric provided to query is not found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/multiseriesScores/¶
List the scores per individual series for the specified multiseries model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/multiseriesScores/?offset=0&limit=100 \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
multiseriesValue | query | string | false | Only the series containing the given value in one of the series ID columns will be returned if specified. |
offset | query | integer | true | The number of results to skip. Defaults to 0 if not specified. |
limit | query | integer | true | The maximum number of results to return. Defaults to 100 if not specified. |
metric | query | string | false | The name of the metric to retrieve the scores for.If omitted, the default project metric will be used. |
orderBy | query | string | false | Used for sorting the series. Supported attributes for ordering include: "multiseriesValue", "rowCount", "validationScore", "holdoutScore" and "backtestingScore", "startDate", "endDate", and "targetAverage".Prefix the attribute name with a dash to sort in descending order,e.g. orderBy=-rowCount . If multiple series with equal values of the ordering attributeexist, ties will be broken arbitrarily. |
filterBy | query | string | false | Used to specify on which attribute values to filter the series.Supported attributes for filtering include: "rowCount", "startDate", "endDate", "targetAverage", "validationScore", "holdoutScore", and "backtestingScore".filterByBins and numberOfBins are required if this parameter is used. |
numberOfBins | query | string | false | Used to specify the number of bins in the histogram on which to filter the series.Can be 10, 20 or 50.filterBy and filterByBins are required if this parameter is used. |
filterByBins | query | string | false | Used to specify the multiseries histogram bins on which to filter the series.filterBy and numberOfBins are required if this parameter is used. |
clusterNames | query | string | false | Used to specify the specific cluster on which to filter the series.filterBy is required if this parameter is used.Only valid for unsupervised clustering projects. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
orderBy | [multiseriesValue , -multiseriesValue , rowCount , -rowCount , startDate , -startDate , endDate , -endDate , targetAverage , -targetAverage , validationScore , -validationScore , backtestingScore , -backtestingScore , holdoutScore , -holdoutScore , cluster , -cluster ] |
filterBy | [rowCount , startDate , endDate , targetAverage , validationScore , backtestingScore , holdoutScore , cluster ] |
numberOfBins | [10 , 20 , 50 ] |
Example responses¶
200 Response
{
"data": [
{
"backtestingScore": 0,
"cluster": "string",
"duration": "string",
"endDate": "2019-08-24T14:15:22Z",
"holdoutScore": 0,
"multiseriesId": "string",
"multiseriesValues": [
"string"
],
"rowCount": 0,
"startDate": "2019-08-24T14:15:22Z",
"targetAverage": "string",
"validationScore": 0
}
],
"next": "string",
"previous": "string",
"querySeriesCount": 0,
"totalSeriesCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve the accuracy scores for each series for the specified multiseries model. | SeriesAccuracyRetrieveResponse |
403 | Forbidden | User does not have permissions to manage models. | None |
404 | Not Found | Model with specified modelId doesn't exist, or user does not have access to the project. |
None |
422 | Unprocessable Entity | Metric provided to query is not found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/datetimeModels/{modelId}/multiseriesScores/¶
Request the computation of per-series scores for a multiseries model. .. note:: Computation uses available partitions only. This endpoint will not compute backtesting scores if no backtesting scores exist prior to this request.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/multiseriesScores/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"computeAllSeries": false
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | SeriesAccuracyCompute | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | Multiseries score computation has been successfully requested. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/multiseriesScores/file/¶
Retrieve the CSV file for the series accuracy.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/multiseriesScores/file/ \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
multiseriesValue | query | string | false | If specified, only the series containing the given value in one of the series ID columns will be returned. |
metric | query | string | false | The name of the metric to retrieve the scores for. If omitted, the default project metric will be used. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | The response will contain a file containing the series accuracy data in csv format. | None |
403 | Forbidden | User does not have permissions to manage models. | None |
404 | Not Found | Model with specified modelId doesn't exist, or user does not have access to the project. |
None |
422 | Unprocessable Entity | Metric provided to query is not found. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
200 | Content-Disposition | string | Contains an auto generated filename for this download ("attachment;filename=Series accuracy (model: |
|
200 | Content-Type | string | MIME type of the returned data |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/externalScores/¶
List of scores on prediction datasets for a project with filtering option by dataset or model or both of them. Prediction dataset may have scores if it contained a column with actual values and predictions were computed on this dataset.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/externalScores/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
datasetId | query | string | false | If provided will return scores for dataset with matching datasetId. |
modelId | query | string | false | If provided will return scores for model with matching modelId. |
projectId | path | string | true | The project ID |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"actualValueColumn": "string",
"datasetId": "string",
"modelId": "string",
"projectId": "string",
"scores": [
{
"label": "string",
"value": 0
}
]
}
],
"next": "string",
"previous": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | List of scores on prediction datasets. | ExternalScoresListResponse |
404 | Not Found | Project not found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/externalScores/¶
Compute model scores for external dataset, first upload your dataset to the project, and then using the corresponding datasetId, compute scores against that dataset. Computing external scores and insights depends on computed prediction, predictions will be computed if they are not available for this dataset. In order to compute scores and insights, uploaded dataset should contain actual value column. This api is not available in time series projects.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/externalScores/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"actualValueColumn": "string",
"datasetId": "string",
"modelId": "string"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
body | body | ExternalScoresCreate | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | none | None |
422 | Unprocessable Entity | The project type does not support or modeling is not finished yet. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/featureAssociationFeaturelists/¶
List all featurelists with feature association matrix availability flags for a project.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/featureAssociationFeaturelists/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
Example responses¶
200 Response
{
"featurelists": [
{
"featurelistId": "string",
"hasFam": true,
"title": "string"
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | List available Feature Association Matrix for a project. | FeatureAssociationListControllerResponse |
404 | Not Found | Project not found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/featureAssociationMatrix/¶
Retrieval for pairwise feature association statistics. Projects created prior to v2.17 are not supported by this feature.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/featureAssociationMatrix/?type=association&metric=mutualInfo \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
type | query | string | true | the type of dependence for the data. Must be either association or correlation . Since v2.19 this is optional and defaults to association . |
metric | query | string | true | the name of a metric to get pairwise data for. Must be one of mutualInfo , cramersV , spearman , pearson , or tau . Since v2.19 this is optional and defaults to mutualInfo . |
featurelistId | query | string | false | the feature list to lookup FAM data for. By default, depending on the type of the project Informative Features or Timeseries Informative Features list will be used. |
projectId | path | string | true | The project ID |
Enumerated Values¶
Parameter | Value |
---|---|
type | [association , correlation ] |
metric | [mutualInfo , cramersV , spearman , pearson , tau ] |
Example responses¶
200 Response
{
"features": [
{
"alphabeticSortIndex": 0,
"clusterId": 0,
"clusterName": "string",
"clusterSortIndex": 0,
"feature": "string",
"importanceSortIndex": 0,
"strengthSortIndex": 0
}
],
"strengths": [
{
"feature1": "string",
"feature2": "string",
"statistic": 0
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve Feature Association Matrix for project. | FeatureAssociationRetrieveControllerResponse |
404 | Not Found | Wrong query parameters specified or no such projectId exists. |
None |
422 | Unprocessable Entity | The project does not support feature associations. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/featureAssociationMatrix/¶
Compute feature association matrix for given featurelist.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/featureAssociationMatrix/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"featurelistId": "string"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
body | body | FeatureAssociationCreatePayload | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | none | None |
404 | Not Found | A project with projectId or a featurelist with featurelistId was not found. |
None |
422 | Unprocessable Entity | The feature association matrix calculation is not supported for this project. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/featureAssociationMatrixDetails/¶
Retrieval for feature association plotting between a pair of features. Projects created prior to v2.17 are not supported by this feature.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/featureAssociationMatrixDetails/?feature1=string&feature2=string \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
feature1 | query | string | true | The name of a feature. |
feature2 | query | string | true | the name of another feature. |
featurelistId | query | string | false | the feature list to lookup FAM data for. By default, depending on the type of the project Informative Features or Timeseries Informative Features list will be used. |
projectId | path | string | true | The project ID |
Example responses¶
200 Response
{
"chartType": "string",
"features": [
"string"
],
"types": [
"CATEGORICAL"
],
"values": [
[
"string"
]
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieval for feature association plotting between a pair of features. | FeatureAssociationDetailsRetrieveControllerResponse |
404 | Not Found | Wrong query parameters specified or no such projectId exists. |
None |
422 | Unprocessable Entity | This project does not support feature associations, (e.g. multilabel, multiseries, time series unsupervised projects.). | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/features/{featureName}/frequentValues/¶
Retrieve the frequent values information for a particular feature. Only valid for numeric features. This route returns information about the frequent values seen for a particular feature, based on the EDA sample of the dataset. Up to 60 values will be returned, and when more values are present, they will be bucketed into a level called "==All Other==" at the end of the response.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/features/{featureName}/frequentValues/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | project id |
featureName | path | string | true | name of the feature |
Example responses¶
200 Response
{
"frequentValues": [
{
"count": 0,
"dataQuality": "string",
"target": 0,
"value": 0
}
],
"name": "string",
"numRows": 0,
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve the frequent values information for a particular feature. | FrequentValuesResponse |
404 | Not Found | If the feature doesn't exist, or no such projectId exists | None |
422 | Unprocessable Entity | If the feature isn't numeric | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/geometryFeaturePlots/¶
Create a map of one location feature
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/geometryFeaturePlots/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"feature": "string"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | Project Id. It is the project to select the location feature from. |
body | body | GeometryFeaturePLotCreatePayload | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | Create a map of one location feature | None |
422 | Unprocessable Entity | Unprocessed Entity | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/geometryFeaturePlots/{featureName}/¶
Retrieve a map of one location feature
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/geometryFeaturePlots/{featureName}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | Project Id. It is the project to select the feature from. |
featureName | path | string | true | Name of location feature to plot on map. Must be supplied in order to determine which plot to retrieve. |
Example responses¶
200 Response
{
"feature": "string",
"plotData": {
"aggregation": "grid",
"bbox": {},
"features": [
{
"geometry": {
"coordinates": [
{}
],
"type": "Point"
},
"properties": {
"count": 0
},
"type": "string"
}
],
"summary": {
"maxCount": 0,
"minCount": 0,
"totalCount": 0
},
"type": "string",
"valueAggregation": "geometry"
},
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve the map of one location feature | GeometryFeaturePlotRetrieveResponse |
404 | Not Found | Map of feature not found | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/anomalyAssessmentInitialization/¶
Initialize the anomaly assessment insight and calculate Shapley explanations for the most anomalous points in the subset. The insight is available for anomaly detection models in time series unsupervised projects which also support calculation of Shapley values.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/anomalyAssessmentInitialization/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"backtest": 19,
"seriesId": "string",
"source": "training"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | AnomalyAssessmentInitialize | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | Job submitted. See Location header. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/anomalyInsightsFile/¶
Retrieve a CSV file of the raw data displayed with the anomaly score from the specific model. The number of rows included will be set by the expected outlier fraction but up to a maximum of 1000 rows. Only models built from anomaly detection blueprints have those insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/anomalyInsightsFile/ \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
filename | query | string | false | name of the file to generate and return |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Responses¶
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/anomalyInsightsTable/¶
Retrieve a table of the raw data displayed with the anomaly score from the specific model. The number of rows displayed is limited to 100 rows by the ANOMALY_INSIGHT_SAMPLE_ROW_COUNT configuration setting. Additionally, feature column count and the size of data in text fields is also limited. Only models built from anomaly detection blueprints have those insights.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/anomalyInsightsTable/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
anomalyScoreRounding | query | integer | false | number of decimals each element anomalyScore column will be rounded to. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"modelId": "string",
"table": [
{
"columns": [
"string"
],
"data": [
0
],
"rowId": [
0
]
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve a table of the raw data displayed with the anomaly score from the specific model. | AnomalyInsightTableRetrieve |
404 | Not Found | The model doesn't have anomaly insights table. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/clusterInsights/¶
Retrieve all computed Cluster Insights for a clustering project model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/clusterInsights/?limit=15 \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | true | At most this many results are returned. The default may change without notice. |
orderBy | query | string | false | Order results by the specified field value. |
searchFor | query | string | false | Search for a specific string in a feature name.This search is case insensitive. If not specified, all features will be returned. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
orderBy | [featureImpact , -featureImpact , featureName , -featureName ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"featureImpact": 0,
"featureName": "string",
"featureType": "image",
"insights": [
{
"allData": {
"images": [
"string"
],
"percentageOfMissingImages": 100
},
"insightName": "representativeImages",
"perCluster": [
{
"clusterName": "string",
"images": [
"string"
],
"percentageOfMissingImages": 100
}
]
}
]
}
],
"isCurrentClusterInsightVersion": true,
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0,
"version": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Insights for a clustering project model. | ClusterInsightsPaginatedResponse |
404 | Not Found | The project or the model was not found or insights have not been computed yet. | None |
422 | Unprocessable Entity | Feature Impact is required. Please, compute it first. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/clusterInsights/¶
Compute Cluster Insights for a clustering project model.The number of features computed for cluster insights are capped at 100, starting with the features used to train the model sorted by feature impact (high to low), and then the remaining features in the dataset alphabetically.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/clusterInsights/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | Empty | false | none |
Example responses¶
202 Response
{}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | A URI of the newly submitted job in the "Location" header. | Empty |
404 | Not Found | The project or the model was not found or insights have not been computed yet. | None |
422 | Unprocessable Entity | Feature Impact is already in progress or Cluster Insighst is already in progress, but we were unable to find the previous job. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/clusterInsights/download/¶
Download all computed Cluster Insights for a clustering project model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/clusterInsights/download/ \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
format | query | string | false | A format to use. |
featurelistId | query | string | false | The ID of the featurelist to download data for. If not specified all columns will be downloaded. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
format | CSV |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | A file with insights for a clustering project model. | None |
404 | Not Found | The project or the model was not found or insights have not been computed yet. | None |
422 | Unprocessable Entity | Feature Impact is required. Please, compute it first. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
200 | Content-Disposition | string | Contains an auto generated filename for this download ("attachment;filename=cluster_insights_ |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/confusionCharts/¶
Retrieve all available confusion charts for model. The response will include a json array of all available confusion charts, in the same format as the response from [GET /api/v2/projects/{projectId}/models/{modelId}/confusionCharts/{source}/][get-apiv2projectsprojectidmodelsmodelidconfusionchartssource]. .. note:: Available for multiclass projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/confusionCharts/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"charts": [
{
"columns": [
0
],
"data": {
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
},
"globalMetrics": {
"f1": 0,
"precision": 0,
"recall": 0
},
"numberOfClasses": 0,
"rows": [
0
],
"source": "validation",
"totalMatrixSum": 0
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | All of the available confusion charts for a model. | ModelConfusionChartListResponse |
404 | Not Found | No confusion chart available. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/confusionCharts/{source}/¶
Retrieve the confusion chart data from a single source. A confusion chart consists of the confusion matrix for all classes, classes frequencies and `oneVsAll` metrics for all classes. The confusion matrix can be requested in a particular sort order and orientated by rows or columns. A subset of the confusion matrix can also be requested in part by specifying slicing indices. Throughout the following specification, `C` refers to the total number of classes in the dataset. The full confusion matrix refers to the confusion matrix with `C` classes. .. note:: Available for multiclass projects only. An example on the meaning of wasActualPercentages and wasPredictedPercentages: Let's say we have the following data: .. code-block:: js classMetrics.classA.wasActualPercentages[0].percentage = 0.56 classMetrics.classA.wasPredictedPercentages[0].percentage = 0.62 classA.wasActualPercentages[0].otherClassName = "classB" classA.wasPredictedPercentages[0].otherClassName = "classB" That means: 1) "Given that it was actually classA, it predicted classB 56% of the time". 2) "Given that classA was predicted, it was actually classB 62% of the time".
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/confusionCharts/{source}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
orderBy | query | string | false | Ordering the chart data by following attributes.Prefix the attribute name with a dash to sort in descending order, e.g. orderBy='-predictedCount' |
orientation | query | string | false | Determines whether the values in the rows of the confusion matrix should correspond to the same actual class ('actual') or predicted class ('predicted'). |
rowStart | query | integer | false | start index of row for slicing the confusion matrix. |
rowEnd | query | integer | false | end index of row for slicing the confusion matrix. |
colStart | query | integer | false | start index of column for slicing the confusion matrix. |
colEnd | query | integer | false | end index of column for slicing the confusion matrix. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
source | path | string | true | Source of the data |
Enumerated Values¶
Parameter | Value |
---|---|
orderBy | [className , -className , actualCount , -actualCount , predictedCount , -predictedCount , f1 , -f1 , precision , -precision , recall , -recall ] |
orientation | [actual , -actual , predicted , -predicted ] |
source | [validation , crossValidation , holdout , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
Example responses¶
200 Response
{
"columns": [
0
],
"data": {
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
},
"globalMetrics": {
"f1": 0,
"precision": 0,
"recall": 0
},
"numberOfClasses": 0,
"rows": [
0
],
"source": "validation",
"totalMatrixSum": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | The confusion chart data from a single source. | ModelConfusionChartRetrieveResponse |
404 | Not Found | No confusion chart for source. | None |
422 | Unprocessable Entity | Invalid indices for confusion matrix. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/confusionCharts/{source}/classDetails/¶
Calculates and sends frequency of class in distributed among other classes for actual and predicted data. A confusion chart class details for given class gives stats of misclassification done by model for given class for actual and predicted data. .. note:: Available for multiclass projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/confusionCharts/{source}/classDetails/?className=string \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
className | query | string | true | Name of a class for which distribution frequency is requested. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
source | path | string | true | Source of the data |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
Example responses¶
200 Response
{
"actualFrequency": [
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
],
"className": "string",
"predictedFrequency": [
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | The details of the confusion matrix of a model for a specific class. | ModelConfusionChartClassDetailsRetrieveReponseController |
404 | Not Found | No confusion chart for source. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/confusionCharts/{source}/metadata/¶
Retrieve metadata for the confusion chart of a model. .. note:: Available for multiclass projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/confusionCharts/{source}/metadata/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
orderBy | query | string | false | Ordering the chart data by following attributes.Prefix the attribute name with a dash to sort in descending order, e.g. orderBy='-predictedCount' |
orientation | query | string | false | Determines whether the values in the rows of the confusion matrix should correspond to the same actual class ('actual') or predicted class ('predicted'). |
thumbnailCellSize | query | integer | false | Number of classes in a single 'thumbnail' cell. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
source | path | string | true | Source of the data |
Enumerated Values¶
Parameter | Value |
---|---|
orderBy | [className , -className , actualCount , -actualCount , predictedCount , -predictedCount , f1 , -f1 , precision , -precision , recall , -recall ] |
orientation | [actual , -actual , predicted , -predicted ] |
source | [validation , crossValidation , holdout , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
Example responses¶
200 Response
{
"classNames": [
"string"
],
"globalMetrics": {
"f1": 0,
"precision": 0,
"recall": 0
},
"relevantClassesPositions": [
[
1
]
],
"source": "validation",
"totalMatrixSum": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | The metadata for the confusion chart of a model. | ModelConfusionChartMetadataRetrieveResponse |
404 | Not Found | No confusion chart for source. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/crossClassAccuracyScores/¶
Retrieves a list of Cross Class Accuracy scores for the model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/crossClassAccuracyScores/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of items to skip. Defaults to 0 if not provided. |
limit | query | integer | false | Number of items to return, defaults to 100 if not provided. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"feature": "string",
"modelId": "string",
"perClassAccuracyScores": [
{
"className": "string",
"metrics": [
{
"metric": "AUC",
"value": 1
}
]
}
],
"predictionThreshold": 1
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Returns Cross Class Accuracy scores. | CrossClassAccuracyList |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/crossClassAccuracyScores/¶
Submits a job to start Cross Class Accuracy scores calculations for the model.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/crossClassAccuracyScores/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
202 Response
{
"statusId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | Job submitted. See Location header. | CrossClassAccuracyCreateResponse |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/dataDisparityInsights/¶
Retrieve a list of Cross Class Data Disparity insights for the model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/dataDisparityInsights/?feature=string&className1=string&className2=string \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of items to skip. Defaults to 0 if not provided. |
limit | query | integer | false | Number of items to return, defaults to 100 if not provided. |
feature | query | string | true | Feature for which insight is computed. |
className1 | query | string | true | One of the compared classes. |
className2 | query | string | true | Another compared class. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"count": 0,
"data": {
"features": [
{
"detailsHistogram": [
{
"bars": [
{
"label": "string",
"value": 0
}
],
"bin": "string"
}
],
"disparityScore": 0,
"featureImpact": 0,
"name": "string",
"status": "Healthy"
}
],
"metric": "string",
"protectedFeature": "string",
"values": [
{
"count": 0,
"label": "string"
}
]
},
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Returns Cross Class Data Disparity results. | DataDisparityRetrieveResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/dataDisparityInsights/¶
Submits a job to start Cross Class Data Disparity insight calculations.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/dataDisparityInsights/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"comparedClassNames": [
"string",
"string"
],
"feature": "string"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | DataDisparityCreatePayload | false | none |
Example responses¶
202 Response
{
"statusId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | Job submitted. See Location header. | DataDisparityCreateResponse |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/datasetConfusionCharts/¶
List of Confusion Charts objects on external datasets for a project with filtering option by dataset. Prediction dataset may have Confusion Chart for multiclass projects computed if it contained a target with actual values and insights were computed on this dataset. A confusion chart consists of the confusion matrix for all classes, classes frequencies and oneVsAll metrics for all classes. The confusion matrix can be requested in a particular sort order and orientated by rows or columns. Available for multiclass projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/datasetConfusionCharts/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
orderBy | query | string | false | Ordering the chart data by following attributes.Prefix the attribute name with a dash to sort in descending order, e.g. orderBy='-predictedCount' |
orientation | query | string | false | Determines whether the values in the rows of the confusion matrix should correspond to the same actual class ('actual') or predicted class ('predicted'). |
rowStart | query | integer | false | start index of row for slicing the confusion matrix. |
rowEnd | query | integer | false | end index of row for slicing the confusion matrix. |
colStart | query | integer | false | start index of column for slicing the confusion matrix. |
colEnd | query | integer | false | end index of column for slicing the confusion matrix. |
datasetId | query | string | false | The datasetId to retrieve a Confusion chart from. |
projectId | path | string | true | The project to retrieve a Confusion chart from. |
modelId | path | string | true | The model to retrieve a Confusion chart from. |
Enumerated Values¶
Parameter | Value |
---|---|
orderBy | [className , -className , actualCount , -actualCount , predictedCount , -predictedCount , f1 , -f1 , precision , -precision , recall , -recall ] |
orientation | [actual , -actual , predicted , -predicted ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"columns": [
0
],
"data": {
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
},
"globalMetrics": {
"f1": 0,
"precision": 0,
"recall": 0
},
"numberOfClasses": 0,
"rows": [
0
],
"source": "validation",
"totalMatrixSum": 0
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | List of Confusion Charts objects for external datasets. | ConfusionChartForDatasetsListResponse |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/datasetConfusionCharts/{datasetId}/¶
Retrieve Confusion Chart objects on external datasets for a project. Prediction dataset may have Confusion Chart for multiclass projects computed if it contained a target with actual values and insights were computed on this dataset. A confusion chart consists of the confusion matrix for all classes, classes frequencies and oneVsAll metrics for all classes. The confusion matrix can be requested in a particular sort order and oriented by rows or columns (zero-indexed). Available for multiclass projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/datasetConfusionCharts/{datasetId}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
orderBy | query | string | false | Ordering the chart data by following attributes.Prefix the attribute name with a dash to sort in descending order, e.g. orderBy='-predictedCount' |
orientation | query | string | false | Determines whether the values in the rows of the confusion matrix should correspond to the same actual class ('actual') or predicted class ('predicted'). |
rowStart | query | integer | false | start index of row for slicing the confusion matrix. |
rowEnd | query | integer | false | end index of row for slicing the confusion matrix. |
colStart | query | integer | false | start index of column for slicing the confusion matrix. |
colEnd | query | integer | false | end index of column for slicing the confusion matrix. |
projectId | path | string | true | The project to retrieve a Confusion chart from. |
modelId | path | string | true | The model to retrieve a Confusion chart from. |
datasetId | path | string | true | The dataset to retrieve a Confusion chart from. |
Enumerated Values¶
Parameter | Value |
---|---|
orderBy | [className , -className , actualCount , -actualCount , predictedCount , -predictedCount , f1 , -f1 , precision , -precision , recall , -recall ] |
orientation | [actual , -actual , predicted , -predicted ] |
Example responses¶
200 Response
{
"columns": [
0
],
"data": {
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
},
"datasetId": "string",
"numberOfClasses": 0,
"rows": [
0
],
"totalMatrixSum": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve Confusion Chart objects on external datasets. | ConfusionChartRetrieveForDatasets |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/datasetConfusionCharts/{datasetId}/classDetails/¶
Calculate and sends frequency of class in distributed among other classes for actual and predicted data. A confusion chart class details for given class gives stats of misclassification done by model for given class for actual and predicted data. Available for multiclass projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/datasetConfusionCharts/{datasetId}/classDetails/?className=string \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
className | query | string | true | Name of a class for which distribution frequency is requested. |
projectId | path | string | true | The project to retrieve a Confusion chart from. |
modelId | path | string | true | The model to retrieve a Confusion chart from. |
datasetId | path | string | true | The dataset to retrieve a Confusion chart from. |
Example responses¶
200 Response
{
"actualFrequency": [
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
],
"className": "string",
"datasetId": "string",
"modelId": "string",
"predictedFrequency": [
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
],
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | A confusion chart class details for given class. | ModelConfusionChartClassDetailsForDatasetRetrieve |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/datasetConfusionCharts/{datasetId}/metadata/¶
Retrieve metadata for the confusion chart of a model on external dataset for a project. Available for multiclass projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/datasetConfusionCharts/{datasetId}/metadata/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
orderBy | query | string | false | Ordering the chart data by following attributes.Prefix the attribute name with a dash to sort in descending order, e.g. orderBy='-predictedCount' |
orientation | query | string | false | Determines whether the values in the rows of the confusion matrix should correspond to the same actual class ('actual') or predicted class ('predicted'). |
thumbnailCellSize | query | integer | false | Number of classes in a single 'thumbnail' cell. |
projectId | path | string | true | The project to retrieve a Confusion chart from. |
modelId | path | string | true | The model to retrieve a Confusion chart from. |
datasetId | path | string | true | The dataset to retrieve a Confusion chart from. |
Enumerated Values¶
Parameter | Value |
---|---|
orderBy | [className , -className , actualCount , -actualCount , predictedCount , -predictedCount , f1 , -f1 , precision , -precision , recall , -recall ] |
orientation | [actual , -actual , predicted , -predicted ] |
Example responses¶
200 Response
{
"classNames": [
"string"
],
"datasetId": "string",
"modelId": "string",
"projectId": "string",
"relevantClassesPositions": [
[
0
]
],
"totalMatrixSum": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve metadata for the Confusion Chart objects on external datasets. | ConfusionChartRetrieveMetadataForDatasets |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/datasetLiftCharts/¶
List of Lift chart objects on prediction datasets for a project with filtering option by dataset. Prediction dataset may have Lift chart computed if it contained a column with actual values and predictions were computed on this dataset. This controller is not supported for multiclass classification projects. For multiclass, instead use /projects/
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/datasetLiftCharts/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
datasetId | query | string | false | If provided will return Lift chart for dataset with matching datasetId. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"datasetId": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve List of Lift chart data on prediction datasets. | LiftChartForDatasetsList |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/datasetMulticlassLiftCharts/¶
List of Multiclass Lift chart objects on prediction datasets for a project with filtering option by dataset. Prediction dataset may have Multiclass Lift chart computed if it contained a column with actual values and predictions were computed on this dataset. Multiclass Lift charts are supported for multiclass classification projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/datasetMulticlassLiftCharts/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
datasetId | query | string | false | If provided will return Lift chart for dataset with matching datasetId. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"classBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
],
"datasetId": "string"
}
],
"modelId": "string",
"next": "http://example.com",
"previous": "http://example.com",
"projectId": "string",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve List of Multiclass Lift chart data on prediction datasets. | MulticlassLiftChartForDatasetsList |
404 | Not Found | No insights found. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/datasetResidualsCharts/¶
List of residuals charts objects on prediction datasets for a project with filtering option by dataset. Prediction dataset may have residuals chart computed if it contained a column with actual values and predictions were computed on this dataset. Residuals charts are supported for regression projects only.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/datasetResidualsCharts/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
datasetId | query | string | false | If provided will return ROC curve for dataset with matching datasetId . |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"datasetId": "string",
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
}
],
"modelId": "string",
"next": "http://example.com",
"previous": "http://example.com",
"projectId": "string",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | ResidualsChartForDatasetsList |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/datasetRocCurves/¶
List of ROC curve objects on prediction datasets for a project with filtering option by dataset.
Prediction dataset may have ROC curve computed if it contained a column with actual values and predictions were computed on this dataset. Each ROC curve object includes an array of points showing the performance of the model at different thresholds for classification, and arrays of sample predictions for both the positive and negative classes.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/datasetRocCurves/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
datasetId | query | string | false | If provided will return ROC curve for dataset with matching datasetId . |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"datasetId": "string",
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": {
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
}
],
"next": "http://example.com",
"previous": "http://example.com"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Objects were returned successfully. No objects is a valid case. | RocCurveForDatasetsList |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/fairnessInsights/¶
Retrieve a list of Per Class Bias insights for the model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/fairnessInsights/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of items to skip. Defaults to 0 if not provided. |
limit | query | integer | false | Number of items to return, defaults to 100 if not provided. |
fairnessMetricsSet | query | string | false | Metric to use for calculating fairness. Can be one of proportionalParity , equalParity , predictionBalance , trueFavorableAndUnfavorableRateParity or FavorableAndUnfavorablePredictiveValueParity . Used and required only if Bias & Fairness in AutoML feature is enabled. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
fairnessMetricsSet | [proportionalParity , equalParity , predictionBalance , trueFavorableAndUnfavorableRateParity , favorableAndUnfavorablePredictiveValueParity ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"fairnessMetric": "proportionalParity",
"fairnessThreshold": 0.8,
"modelId": "string",
"perClassFairness": [
{
"absoluteValue": 0,
"className": "string",
"entriesCount": 0,
"isStatisticallySignificant": true,
"value": 1
}
],
"predictionThreshold": 1,
"protectedFeature": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Returns Per Class Bias results. | FairnessInsightsListResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/fairnessInsights/¶
Submits a job to start Per Class Bias insight calculations for the model.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/fairnessInsights/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"fairnessMetricsSet": "proportionalParity"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | FairnessInsightsStartCalculationPayload | false | none |
Example responses¶
202 Response
{
"statusId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | Job submitted. See Location header. | FairnessInsightsStartCalculationResponse |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/featureEffects/¶
Retrieve Feature Effects for the model.
Feature Effects provides partial dependence and predicted vs actual values for the top 500 features, ordered by feature impact score.
The partial dependence shows marginal effect of a feature on the target variable after accounting for the average effects of all other predictive features. It indicates how, holding all other variables except the feature of interest as they were, the value of this feature affects your prediction.
If a Feature Effects job was previously submitted, this endpoint will return a response structured as {"message":
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/featureEffects/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
source | query | string | false | Models data source. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation , holdout ] |
Example responses¶
200 Response
{
"featureEffects": [
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
],
"modelId": "string",
"projectId": "string",
"source": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | FeatureEffectsResponse |
403 | Forbidden | User does not have permission to view the project. | None |
404 | Not Found | Project, model, source or computation results do not exist. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/featureEffects/¶
Add a request to the queue to calculate Feature Effects.
If the job has been previously submitted, the request fails, returning the jobId
of the previously submitted job. Use this jobId
to check status of the previously submitted job.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/featureEffects/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"rowCount": 10
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | FeatureEffectCreate | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The Feature Effects request has been successfully submitted. See Location header. | None |
403 | Forbidden | User does not have permission to view or submit jobs for the project. | None |
404 | Not Found | Provided project or model does not exist. | None |
422 | Unprocessable Entity | Queue submission error. |
.. minversion:: v2.21
If the rowCount exceeds the maximum or minimum value for this dataset. Minimum is 10 rows. Maximum is 100000 rows or the training sample size of the model, whichever is less.|None|
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/featureEffectsMetadata/¶
Retrieve Feature Effects metadata. Response contains status and available sources.
One of the provided source
parameters used for retrieving Feature Effects.
* Source can be, at a minimum, training
or validation
. If holdout is configured for the project, source
also includes holdout
.
* Source value of training
is always available. (versions prior to v2.17 support validation
only)
* When a model is trained into validation
or holdout
without stacked predictions (i.e., no out-of-sample predictions in validation
or holdout
), validation
and holdout
sources are not available.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/featureEffectsMetadata/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"sources": [
"training"
],
"status": "INPROGRESS"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | ModelXrayMetadataResponse |
403 | Forbidden | User does not have permission to view the project. | None |
404 | Not Found | Project or model does not exist. | None |
422 | Unprocessable Entity | The model is datetime partitioned. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/featureImpact/¶
Retrieve feature impact scores for features in a model.
Feature Impact is computed for each column by creating new data with that column randomly permuted (but the others left unchanged), and seeing how the error metric score for the predictions is affected. Elsewhere this technique is sometimes called 'Permutation Importance'.
The impactUnnormalized
is how much worse the error metric score is when making predictions on this modified data. The impactNormalized
is normalized so that the largest value is 1. In both cases, larger values indicate more important features. If a feature is a redundant feature, i.e. once other features are considered it doesn't contribute much in addition, the redundantWith
value is the name of feature that has the highest correlation with this feature.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/featureImpact/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
backtest | query | any | false | The backtest value used for Feature Impact computation. Applicable for datetime aware models. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"backtest": 19,
"count": 0,
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"ranRedundancyDetection": true,
"rowCount": 0,
"shapBased": true
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | PermutationFeatureImpactResponse |
404 | Not Found | No feature impact data found for the given model. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/featureImpact/¶
Add a request to calculate feature impact to the queue.
If the job has been previously submitted, the request will fail and return the jobId
of previously submitted job. This jobId
can be used to check status of previously submitted job.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/featureImpact/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"backtest": 19,
"rowCount": 10
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | PermutationFeatureImpactCreatePayload | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The request was accepted and will be worked on. | None |
404 | Not Found | If modelId does not exist in project leaderboard |
None |
422 | Unprocessable Entity | If feature impact has already run will return error including jobId property which is the jobId of the previously started feature impact job. |
.. minversion:: v2.21
If the rowCount
exceeds the maximum or minimum value for this dataset. Minimum is 10 rows. Maximum is 100000 rows or the training sample size of the model, whichever is less.|None|
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/featureLists/{datasetId}/clusterInsights/¶
Retrieve computed Cluster Insights for a clustering project model on a single featurelist.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/featureLists/{datasetId}/clusterInsights/?limit=15 \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | true | At most this many results are returned. The default may change without notice. |
orderBy | query | string | false | Order results by the specified field value. |
searchFor | query | string | false | Search for a specific string in a feature name.This search is case insensitive. If not specified, all features will be returned. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
datasetId | path | string | true | The dataset ID |
Enumerated Values¶
Parameter | Value |
---|---|
orderBy | [featureImpact , -featureImpact , featureName , -featureName ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"featureImpact": 0,
"featureName": "string",
"featureType": "image",
"insights": [
{
"allData": {
"images": [
"string"
],
"percentageOfMissingImages": 100
},
"insightName": "representativeImages",
"perCluster": [
{
"clusterName": "string",
"images": [
"string"
],
"percentageOfMissingImages": 100
}
]
}
]
}
],
"isCurrentClusterInsightVersion": true,
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0,
"version": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Insights for a clustering project model on a single featurelist. | ClusterInsightsPaginatedResponse |
404 | Not Found | The project or the model was not found or insights have not been computed yet. | None |
422 | Unprocessable Entity | Feature Impact is required. Please, compute it first. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/labelwiseRocCurves/{source}/¶
Retrieve labelwise ROC curves for model and given source.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/labelwiseRocCurves/{source}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
labels | query | string | false | Labels for which data is requested. |
searchQuery | query | string | false | Search query for label. |
sortBy | query | string | false | Property to sort labels in the response. |
sortOrder | query | string | false | Sort order. |
threshold | query | number | false | Threshold at which the metric should be sorted. |
offset | query | integer | false | Number of labels to skip. |
limit | query | integer | false | Number of labels to return. |
includeModelAverage | query | boolean | false | Whether model average metrics should be included in the response. |
projectId | path | string | true | Project Id. |
modelId | path | string | true | Model Id. |
source | path | string | true | Chart source. |
Enumerated Values¶
Parameter | Value |
---|---|
sortBy | [accuracy , f1Score , falsePositiveRate , label , matthewsCorrelationCoefficient , negativePredictiveValue , positivePredictiveValue , trueNegativeRate , truePositiveRate ] |
sortOrder | [ascending , descending ] |
source | [validation , crossValidation , holdout ] |
Example responses¶
200 Response
{
"averageModelMetrics": {
"metrics": [
{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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{
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"numLabelsUsedInCalculation": 0,
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},
{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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},
{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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}
],
"source": "validation",
"thresholds": [
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},
"charts": [
{
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"label": "string",
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 1,
"f1Score": 1,
"falseNegativeScore": 0,
"falsePositiveRate": 1,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": -1,
"negativePredictiveValue": 1,
"positivePredictiveValue": 1,
"threshold": 2,
"trueNegativeRate": 1,
"trueNegativeScore": 0,
"truePositiveRate": 1,
"truePositiveScore": 0
}
],
"source": "validation"
}
],
"count": 0,
"labels": [
"string"
],
"next": "http://example.com",
"previous": "http://example.com",
"rocType": "binary",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Labelwise ROC curves for model and given source. | LabelwiseROC |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/liftChart/¶
Retrieve all available lift charts for model. The response will include a json list of all available lift charts, in the same format as the response from GET /api/v2/projects/{projectId}/models/{modelId}/liftChart/{source}/.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/liftChart/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"charts": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"source": "validation"
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | A list of all of the available lift charts for a model. | ModelLiftChartListResponse |
403 | Forbidden | Invalid Permissions | None |
404 | Not Found | Please use multiclass lift route for per-class lift data. | None |
422 | Unprocessable Entity | Lift chart is not available for unsupervised mode projects. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/liftChart/{source}/¶
Retrieve the lift chart data from a single source.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/liftChart/{source}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
source | path | string | true | Source of the data |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
Example responses¶
200 Response
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"source": "validation"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Lift chart data from a single source. | ModelLiftChartResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/multiclassFeatureEffects/¶
Retrieve feature effects for each class in a multiclass model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/multiclassFeatureEffects/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
source | query | string | false | Models data source. |
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
class | query | string | false | Target class label. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
source | [training , validation , holdout ] |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"class": "string",
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
],
"modelId": "string",
"next": "http://example.com",
"previous": "http://example.com",
"projectId": "string",
"source": "string",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | MulticlassFeatureEffectsResponse |
403 | Forbidden | User does not have permission to view the project. | None |
404 | Not Found | Project, model, source or computation results do not exist. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/multiclassFeatureEffects/¶
Compute feature effects for a multiclass model. If the job has been previously submitted, the request fails, returning the jobId
of the previously submitted job. Use this jobId
to check status of the previously submitted job.
NOTE: feature effects are computed for top 100 classes.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/multiclassFeatureEffects/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"features": [
"string"
],
"rowCount": 10,
"topNFeatures": 0
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | MulticlassFeatureEffectCreate | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | The Feature Effects request has been successfully submitted. See Location header. | None |
403 | Forbidden | User does not have permission to view or submit jobs for the project. | None |
404 | Not Found | Project, model, source or computation results do not exist. | None |
422 | Unprocessable Entity | Queue submission error. If the rowCount exceeds the maximum or minimum value for this dataset. Minimum is 10 rows. Maximum is 100000 rows or the training sample size of the model, whichever is less. If neither features nor topNFeatures is provided. |
None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/multiclassFeatureImpact/¶
Retrieve feature impact scores for each class in a multiclass model.
Feature Impact is computed for each column by creating new data with that column randomly permuted (but the others left unchanged), and seeing how the error metric score for the predictions is affected. Elsewhere this technique is sometimes called 'Permutation Importance'.
The impactUnnormalized
is how much worse the error metric score is when making predictions on this modified data. The impactNormalized
is normalized so that the largest value is 1. In both cases, larger values indicate more important features.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/multiclassFeatureImpact/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"classFeatureImpacts": [
{
"class": "string",
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
]
}
],
"count": 0,
"next": "http://example.com",
"previous": "http://example.com",
"ranRedundancyDetection": true,
"shapBased": true
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | MulticlassFeatureImpactResponse |
404 | Not Found | If no feature impact data found for a given model. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/multiclassLiftChart/¶
Retrieve all available lift charts for multiclass model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/multiclassLiftChart/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"charts": [
{
"classBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
],
"source": "validation"
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Multiclass lift chart data. | AllMulticlassModelLiftChartsResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/multiclassLiftChart/{source}/¶
Retrieve the multiclass lift chart data from a single source.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/multiclassLiftChart/{source}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
source | path | string | true | Source of the data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout ] |
Example responses¶
200 Response
{
"classBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
],
"source": "validation"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Multiclass lift chart data from a single source. | MulticlassModelLiftChartResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/multilabelLiftCharts/{source}/¶
Retrieve labelwise lift charts for model and given source.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/multilabelLiftCharts/{source}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
labels | query | string | false | Labels for which data is requested. |
projectId | path | string | true | Project Id. |
modelId | path | string | true | Model Id. |
source | path | string | true | Chart source. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout ] |
Example responses¶
200 Response
{
"labelBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"label": "string"
}
],
"labels": [
"string"
],
"modelId": "string",
"projectId": "string",
"source": "validation"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Labelwise lift charts for model and given source. | LabelwiseLiftChart |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/residuals/¶
Retrieve all residuals charts for a model.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/residuals/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"residuals": {
"crossValidation": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"holdout": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"validation": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
}
}
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | ModelResidualsList |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/residuals/{source}/¶
Retrieve the residuals chart data from a single source.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/residuals/{source}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
source | path | string | true | Source of the data. |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout ] |
Example responses¶
200 Response
{
"residuals": {
"crossValidation": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"holdout": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"validation": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
}
}
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | ModelResidualsList |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/rocCurve/¶
Retrieve all available ROC curves for model. The response will include a json list of all available ROC curves, in the same format as the response from GET /api/v2/projects/{projectId}/models/{modelId}/rocCurve/{source}/.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/rocCurve/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"charts": [
{
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
],
"source": "validation"
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | A list of all of the available ROC curves for a model. | ModelRocCurveListResponse |
403 | Forbidden | Invalid Permissions | None |
404 | Not Found | This resource does not exist. | None |
422 | Unprocessable Entity | Unsupervised mode projects do not have ROC curves | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/rocCurve/{source}/¶
Retrieve the ROC curve data from a single source. The response includes an array of pointsshowing the performance of the model at different thresholds for classification, and arrays of sample predictions for both the positive and negative classes.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/rocCurve/{source}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
source | path | string | true | Source of the data |
Enumerated Values¶
Parameter | Value |
---|---|
source | [validation , crossValidation , holdout , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
Example responses¶
200 Response
{
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
],
"source": "validation"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | ROC curve data from a single source. | ModelRocCurveResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/shapImpact/¶
Retrieve Feature Impact for a model. SHAP impact is computed by calculating the shap values on a sample of training data and then taking the mean absolute value for each column. The larger the impact value, the more important the feature. DEPRECATED: Use the componentized route instead: GET /api/v2/insights/shapImpact/models/{entityId}/
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/shapImpact/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Example responses¶
200 Response
{
"count": 0,
"rowCount": 0,
"shapImpacts": [
{
"featureName": "string",
"impactNormalized": 0,
"impactUnnormalized": 0
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Retrieve Feature Impact for a model. | ShapImpactRetrieveResponse |
400 | Bad Request | Request for multiclass project | None |
404 | Not Found | No Shapley-based impact values calculated for this model | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/models/{modelId}/shapImpact/¶
Create SHAP-based Feature Impact for the model. DEPRECATED: Use the componentized route instead: POST /api/v2/insights/shapImpact/
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/shapImpact/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"rowCount": 10
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
body | body | FeatureImpactCreatePayload | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | none | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/models/{modelId}/wordCloud/¶
Retrieve word cloud data for a model. Not all models will have word cloud data available, even when they use text features.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/wordCloud/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
excludeStopWords | query | string | false | Set to true if you want stopwords excluded from the response. |
projectId | path | string | true | The project ID |
modelId | path | string | true | The model ID |
Enumerated Values¶
Parameter | Value |
---|---|
excludeStopWords | [false , False , true , True ] |
Example responses¶
200 Response
{
"ngrams": [
{
"class": "string",
"coefficient": -1,
"count": 0,
"frequency": 0,
"isStopword": true,
"ngram": "string",
"variable": "string"
}
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | WordCloudRetrieveResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/multicategoricalInvalidFormat/¶
Retrieve multicategorical data quality log.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/multicategoricalInvalidFormat/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The ID of the project this request is associated with. |
Example responses¶
200 Response
{
"data": {
"errors": [
{
"error": "string",
"feature": "string",
"rowData": "string",
"rowIndex": 0
}
]
},
"projectId": "string"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Data quality log for multicategorical features. | MulticategoricalInvalidFormatResponse |
422 | Unprocessable Entity | Not a data quality enabled project | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/multicategoricalInvalidFormat/file/¶
Get file with format errors of potential multicategorical features.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/multicategoricalInvalidFormat/file/ \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The ID of the project this request is associated with. |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | File with format errors of potential multicategorical features. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/payoffMatrices/¶
List of all payoff matrices for a project.
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/payoffMatrices/?offset=0&limit=100 \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | true | Number of payoff matrices to skip. |
limit | query | integer | true | Number of payoff matrices to return. |
projectId | path | string | true | The project ID |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"falseNegativeValue": 0,
"falsePositiveValue": 0,
"id": "string",
"name": "string",
"projectId": "string",
"trueNegativeValue": 0,
"truePositiveValue": 0
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | List of payoff matrices. | PayoffMatricesListResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/payoffMatrices/¶
Create a payoff matrix associated with a project.
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/payoffMatrices/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"falseNegativeValue": 0,
"falsePositiveValue": 0,
"name": "string",
"trueNegativeValue": 0,
"truePositiveValue": 0
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
body | body | PayoffMatricesCreate | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
201 | Created | none | None |
409 | Conflict | Conflict occurred: [Error details from exception] | None |
422 | Unprocessable Entity | - This route is only allowed for binary classification projects. | |
- Error occurred during processing: [Error details from exception] | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
DELETE /api/v2/projects/{projectId}/payoffMatrices/{payoffMatrixId}/¶
Delete a payoff matrix in a project.
Code samples¶
# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/projects/{projectId}/payoffMatrices/{payoffMatrixId}/ \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
payoffMatrixId | path | string | true | ObjectId of the payoff matrix. |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
204 | No Content | Payoff matrix deleted successfully. | None |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
PUT /api/v2/projects/{projectId}/payoffMatrices/{payoffMatrixId}/¶
Update all fields in a payoff matrix, including values and label.
Code samples¶
# You can also use wget
curl -X PUT https://app.datarobot.com/api/v2/projects/{projectId}/payoffMatrices/{payoffMatrixId}/ \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"falseNegativeValue": 0,
"falsePositiveValue": 0,
"name": "string",
"trueNegativeValue": 0,
"truePositiveValue": 0
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
payoffMatrixId | path | string | true | ObjectId of the payoff matrix. |
body | body | PayoffMatricesCreate | false | none |
Example responses¶
200 Response
{
"falseNegativeValue": 0,
"falsePositiveValue": 0,
"id": "string",
"name": "string",
"projectId": "string",
"trueNegativeValue": 0,
"truePositiveValue": 0
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | Updated payoff matrix values and label. | PayoffMatricesResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/shapMatrices/¶
Return a list of available SHAP matrix records. DEPRECATED: Use the componentized route instead: GET /api/v2/insights/shapMatrix/models/{entityId}/
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/shapMatrices/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
offset | query | integer | false | Number of results to skip. |
limit | query | integer | false | At most this many results are returned. The default may change without notice. |
projectId | path | string | true | The project ID |
Example responses¶
200 Response
{
"count": 0,
"data": [
{
"datasetId": "string",
"id": "string",
"metadata": {
"maxNormalizedMismatch": 0,
"mismatchRowCount": 0
},
"modelId": "string",
"projectId": "string",
"url": "http://example.com"
}
],
"next": "http://example.com",
"previous": "http://example.com"
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | ShapMatrixListResponse |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
POST /api/v2/projects/{projectId}/shapMatrices/¶
Submit a request to calculate a matrix with SHAP based prediction explanations scores. DEPRECATED: Use the componentized route instead: POST /api/v2/insights/shapMatrix/
Code samples¶
# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/shapMatrices/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer {access-token}" \
-d '{undefined}'
Body parameter¶
{
"datasetId": "string",
"modelId": "string"
}
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID |
body | body | CreateShapMatrixPayload | false | none |
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
202 | Accepted | Job submitted. See Location header. | None |
Response Headers¶
Status | Header | Type | Format | Description |
---|---|---|---|---|
202 | Location | string | A url that can be polled to check the status. |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
GET /api/v2/projects/{projectId}/shapMatrices/{shapMatrixId}/¶
Return matrix with SHAP-based prediction explanations scores. DEPRECATED: Use the componentized route instead: GET /api/v2/insights/shapMatrix/models/{entityId}/
Code samples¶
# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/shapMatrices/{shapMatrixId}/ \
-H "Accept: application/json" \
-H "Authorization: Bearer {access-token}"
Parameters
Name | In | Type | Required | Description |
---|---|---|---|---|
projectId | path | string | true | The project ID. |
shapMatrixId | path | string | true | The SHAP matrix ID. |
Example responses¶
200 Response
{
"columnNames": [
"string"
]
}
Responses¶
Status | Meaning | Description | Schema |
---|---|---|---|
200 | OK | none | string |
To perform this operation, you must be authenticated by means of one of the following methods:
BearerAuth
Schemas¶
AOTChartBins
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actual | number¦null | true | The average actual value of the target in the bin. null if there are no entries in the bin or if this is an anomaly detection project. |
|
endDate | string(date-time) | true | The datetime of the end of the bin (exclusive). | |
frequency | number¦null | true | As indicated by the frequencyType in the Metadata, used to determine what the averages mentioned above are taken over. null if there are no entries in the bin. |
|
predicted | number¦null | true | The average prediction of the model in the bin. null if there are no entries in the bin. |
|
startDate | string(date-time) | true | The datetime of the start of the bin (inclusive). |
AOTChartMetadataDatasetMetadata
{
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
The dataset metadata.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
endDate | string(date-time) | true | ISO-8601 formatted end date (max date) in the dataset. | |
startDate | string(date-time) | true | ISO-8601 formatted start date (min date) in the dataset. |
AOTChartMetadataResponse
{
"datasetId": "string",
"datasetMetadata": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"frequencyType": "rowCount",
"metricName": "string",
"modelId": "string",
"projectId": "string",
"resolutions": [
"microseconds"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
datasetId | string | true | The dataset id which was used to compute the AOT chart. | |
datasetMetadata | AOTChartMetadataDatasetMetadata | true | The dataset metadata. | |
frequencyType | string | true | How to interpret the frequency attribute of each datetimeTrendBin. One of ['rowCount', 'weightedRowCount', 'exposure', 'weightedExposure']. | |
metricName | string | true | The metric used to score each bin and the calculate the metric attribute of each datetimeTrendBin. | |
modelId | string | true | The model id which was used to compute the AOT chart. | |
projectId | string | true | The project id which was used to compute the AOT chart. | |
resolutions | [string] | true | Suggested time resolutions where a resolution is one of ['milliseconds', 'seconds', 'minutes', 'hours', 'days', 'weeks', 'months', 'years']. |
Enumerated Values¶
Property | Value |
---|---|
frequencyType | [rowCount , weightedRowCount , exposure , weightedExposure ] |
AOTChartPreviewResponse
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"datasetId": "string",
"modelId": "string",
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [AOTChartBins] | true | The datetime chart data for that source. | |
datasetId | string | true | The dataset id which was used to compute the AOT chart. | |
modelId | string | true | The model id which was used to compute the AOT chart. | |
projectId | string | true | The project id which was used to compute the AOT chart. |
AOTChartRetrieveResponse
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"datasetId": "string",
"endDate": "2019-08-24T14:15:22Z",
"modelId": "string",
"projectId": "string",
"resolution": "microseconds",
"startDate": "2019-08-24T14:15:22Z",
"statistics": {
"durbinWatson": 0
}
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [AOTChartBins] | true | The datetime chart data for that source. | |
datasetId | string | true | The dataset id to which the chart data belongs. | |
endDate | string(date-time) | false | The requested endDate , or, if not specified, the end date for this dataset (exclusive). Example: '2010-05-13T00:00:00.000000Z'. |
|
modelId | string | true | The model id to which the chart data belongs. | |
projectId | string | true | The project id to which the chart data belongs. | |
resolution | string | true | The resolution used for binning where a resolution is one of ['milliseconds', 'seconds', 'minutes', 'hours', 'days', 'weeks', 'months', 'years']. | |
startDate | string(date-time) | false | The requested startDate , or, if not specified, the start date for this dataset. Example: '2010-05-13T00:00:00.000000Z'. |
|
statistics | AOTChartStatistics | true | Statistics calculated on the chart data. |
Enumerated Values¶
Property | Value |
---|---|
resolution | [microseconds , milliseconds , seconds , minutes , hours , days , weeks , months , quarters , years ] |
AOTChartStatistics
{
"durbinWatson": 0
}
Statistics calculated on the chart data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
durbinWatson | number | true | The Durbin-Watson statistic for the chart data. Value is between 0 and 4. Returns -1 when the statistic is invalid for the data, e.g. if this is an anomaly detection project. |
AccuracyMetrics
{
"metric": "AUC",
"value": 1
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
metric | string | true | The name of the metric. | |
value | number | true | maximum: 1 minimum: 0 |
The calculated score of the metric. |
Enumerated Values¶
Property | Value |
---|---|
metric | [AUC , Weighted AUC , Area Under PR Curve , Weighted Area Under PR Curve , Kolmogorov-Smirnov , Weighted Kolmogorov-Smirnov , FVE Binomial , Weighted FVE Binomial , Gini Norm , Weighted Gini Norm , LogLoss , Weighted LogLoss , Max MCC , Weighted Max MCC , Rate@Top5% , Weighted Rate@Top5% , Rate@Top10% , Weighted Rate@Top10% , Rate@TopTenth% , RMSE , Weighted RMSE , f1 , accuracy ] |
AccuracyOverTimePlotsBins
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actual | number¦null | true | Average actual value of the target in the bin. null if there are no entries in the bin. |
|
endDate | string(date-time) | true | The datetime of the end of the bin (exclusive). | |
frequency | integer¦null | true | Indicates number of values averaged in bin in case of a resolution change. | |
predicted | number¦null | true | Average prediction of the model in the bin. null if there are no entries in the bin. |
|
startDate | string(date-time) | true | The datetime of the start of the bin (inclusive). |
AccuracyOverTimePlotsDataResponse
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"calendarEvents": [
{
"date": "2019-08-24T14:15:22Z",
"name": "string",
"seriesId": "string"
}
],
"endDate": "2019-08-24T14:15:22Z",
"resolution": "milliseconds",
"startDate": "2019-08-24T14:15:22Z",
"statistics": {
"durbinWatson": 4
}
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [AccuracyOverTimePlotsBins] | true | maxItems: 1000 minItems: 1 |
An array of bins for the retrieved plots. |
calendarEvents | [CalendarEvent] | true | maxItems: 1000 |
An array of calendar events for a retrieved plot. |
endDate | string(date-time) | true | The datetime of the end of the chart data (exclusive). | |
resolution | string | true | The resolution that is used for binning. | |
startDate | string(date-time) | true | The datetime of the start of the chart data (inclusive). | |
statistics | AccuracyOverTimePlotsStatistics | true | Statistics calculated for the chart data. |
Enumerated Values¶
Property | Value |
---|---|
resolution | [milliseconds , seconds , minutes , hours , days , weeks , months , quarters , years ] |
AccuracyOverTimePlotsMetadataResponse
{
"backtestMetadata": [
{
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
}
],
"backtestStatuses": [
{
"training": "completed",
"validation": "completed"
}
],
"estimatedSeriesLimit": 1,
"forecastDistance": 1000,
"holdoutMetadata": {
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
},
"holdoutStatuses": {
"training": "completed",
"validation": "completed"
},
"resolutions": [
"milliseconds"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestMetadata | [DatetimeTrendPlotsBacktestMetadata] | true | maxItems: 20 minItems: 1 |
An array of metadata information for each backtest. The array index of metadata object is the backtest index. |
backtestStatuses | [AccuracyOverTimePlotsStatus] | true | maxItems: 20 minItems: 1 |
An array of status information for each backtest. The array index of status object is the backtest index. |
estimatedSeriesLimit | integer | false | minimum: 1 |
Estimated number of series that can be calculated in one request for 1 FD. |
forecastDistance | integer¦null | true | maximum: 1000 minimum: 0 |
The forecast distance for which the data was retrieved. null for OTV projects. |
holdoutMetadata | DatetimeTrendPlotsBacktestMetadata | true | none | |
holdoutStatuses | AccuracyOverTimePlotsStatus | true | none | |
resolutions | [string] | true | maxItems: 9 minItems: 1 |
An array of available time resolutions for which plots can be retrieved. |
AccuracyOverTimePlotsStatistics
{
"durbinWatson": 4
}
Statistics calculated for the chart data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
durbinWatson | number¦null | true | maximum: 4 minimum: 0 |
The Durbin-Watson statistic for the chart data. Value is between 0 and 4. Durbin-Watson statistic is a test statistic used to detect the presence of autocorrelation at lag 1 in the residuals (prediction errors) from a regression analysis. More info https://wikipedia.org/wiki/Durbin%E2%80%93Watson_statistic |
AccuracyOverTimePlotsStatus
{
"training": "completed",
"validation": "completed"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
training | string | true | The status for the training. | |
validation | string | true | The status for the validation. |
Enumerated Values¶
Property | Value |
---|---|
training | [completed , errored , inProgress , insufficientData , notCompleted , notSupported ] |
validation | [completed , errored , inProgress , insufficientData , notCompleted , notSupported ] |
ActualFrequency
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
otherClassName | string | true | The name of the class. | |
percentage | number | true | maximum: 100 minimum: 0 |
The percentage of the times this class was predicted when is was actually classMetrics.className (from 0 to 100). |
value | integer | true | minimum: 0 |
The count of the times this class was predicted when is was actually classMetrics.className . |
ActualPercentages
{
"otherClassName": "string",
"percentage": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
otherClassName | string | true | the name of the class | |
percentage | number | true | The percentage of the times this class was predicted when is was actually classMetrics.className |
AllDataImage
{
"images": [
"string"
],
"percentageOfMissingImages": 100
}
Statistics for all data for different feature values.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
images | [string] | true | maxItems: 10 minItems: 1 |
A list of b64 encoded images. |
percentageOfMissingImages | number | true | maximum: 100 minimum: 0 |
A percentage of image rows that have a missing value for this feature. |
AllDataText
{
"missingRowsPercent": 100,
"perValueStatistics": [
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
]
}
Statistics for all data for different feature values.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
missingRowsPercent | number¦null | false | maximum: 100 minimum: 0 |
A percentage of all rows that have a missing value for this feature. |
perValueStatistics | [PerValueStatisticTextListItem] | true | Statistic value for feature values in all data or a cluster. |
AllMulticlassModelLiftChartsResponse
{
"charts": [
{
"classBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
],
"source": "validation"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
charts | [MulticlassModelLiftChartResponse] | true | List of lift chart data from all available sources. |
AnalyzedFeature
{
"detailsHistogram": [
{
"bars": [
{
"label": "string",
"value": 0
}
],
"bin": "string"
}
],
"disparityScore": 0,
"featureImpact": 0,
"name": "string",
"status": "Healthy"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
detailsHistogram | [HistogramDetails] | true | Histogram details for the specified feature. | |
disparityScore | number | true | A number to describe disparity for the feature between the compared classes. | |
featureImpact | number | true | A feature importance value. | |
name | string | true | Name of the feature. | |
status | string | true | A status of the feature. |
Enumerated Values¶
Property | Value |
---|---|
status | [Healthy , At Risk , Failing ] |
AnomalyAssessmentExplanationsResponse
{
"backtest": 19,
"count": 0,
"data": [
{
"prediction": 0,
"shapExplanation": [
{
"feature": "string",
"featureValue": "string",
"strength": 0
}
],
"timestamp": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"modelId": "string",
"projectId": "string",
"recordId": "string",
"seriesId": "string",
"shapBaseValue": 0,
"source": "training",
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtest | any | true | The backtest of the record. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | maximum: 19 minimum: 0 |
none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | The count of points. | |
data | [DataPointResponse] | true | Each is a DataPoint corresponding to a row in the specified range. |
|
endDate | string(date-time) | true | ISO-formatted last timestamp in the response. For example: 2019-08-30T00:00:00.000000Z . |
|
modelId | string | true | The model ID of the record. | |
projectId | string | true | The project ID of the record. | |
recordId | string | true | The ID of the anomaly assessment record. | |
seriesId | string¦null | true | The series id of the record. Applicable in multiseries projects | |
shapBaseValue | number | true | shap base value | |
source | string | true | The source of the record | |
startDate | string(date-time) | true | ISO-formatted first timestamp in the response. For example: 2019-08-01T00:00:00.000000Z . |
Enumerated Values¶
Property | Value |
---|---|
anonymous | holdout |
source | [training , validation ] |
AnomalyAssessmentInitialize
{
"backtest": 19,
"seriesId": "string",
"source": "training"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtest | any | true | The backtest to compute insight for. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | maximum: 19 minimum: 0 |
none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
seriesId | string | false | Required for multiseries projects. The series id to compute insight for. | |
source | string | true | The source to compute insight for. |
Enumerated Values¶
Property | Value |
---|---|
anonymous | holdout |
source | [training , validation ] |
AnomalyAssessmentPreviewResponse
{
"backtest": 19,
"endDate": "2019-08-24T14:15:22Z",
"modelId": "string",
"previewBins": [
{
"avgPredicted": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"maxPredicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"projectId": "string",
"recordId": "string",
"seriesId": "string",
"source": "training",
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtest | any | true | The backtest of the record. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | maximum: 19 minimum: 0 |
none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
endDate | string(date-time) | true | ISO-formatted last timestamp in the subset. For example: 2019-08-30T00:00:00.000000Z . |
|
modelId | string | true | The model ID of the record. | |
previewBins | [BinResponse] | true | Aggregated predictions for the subset. Bins boundaries may differ from actual start/end dates because this is an aggregation. | |
projectId | string | true | The project ID of the record. | |
recordId | string | true | The ID of the anomaly assessment record. | |
seriesId | string¦null | true | The series id of the record. Applicable in multiseries projects | |
source | string | true | The source of the record | |
startDate | string(date-time) | true | ISO-formatted first timestamp in the subset. For example: 2019-08-01T00:00:00.000000Z . |
Enumerated Values¶
Property | Value |
---|---|
anonymous | holdout |
source | [training , validation ] |
AnomalyAssessmentRecordResponse
{
"backtest": 19,
"deleteLocation": "http://example.com",
"endDate": "2019-08-24T14:15:22Z",
"latestExplanationsLocation": "http://example.com",
"modelId": "string",
"predictionThreshold": 0,
"previewLocation": "http://example.com",
"projectId": "string",
"recordId": "string",
"seriesId": "string",
"source": "training",
"startDate": "2019-08-24T14:15:22Z",
"status": "noData",
"statusDetails": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtest | any | true | The backtest of the record. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | maximum: 19 minimum: 0 |
none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
deleteLocation | string(uri)¦null | true | URL to delete anomaly assessment record. | |
endDate | string(date-time)¦null | true | ISO-formatted last timestamp in the subset. For example: 2019-08-30T00:00:00.000000Z . |
|
latestExplanationsLocation | string(uri)¦null | true | URL to retrieve the latest predictions with the shap explanations. | |
modelId | string | true | The model ID of the record. | |
predictionThreshold | number¦null | true | The threshold, all rows with anomaly scores greater or equal to it have Shapley explanations computed. | |
previewLocation | string(uri)¦null | true | URL to retrieve predictions preview for the record. | |
projectId | string | true | The project ID of the record. | |
recordId | string | true | The ID of the anomaly assessment record. | |
seriesId | string¦null | true | The series id of the record. Applicable in multiseries projects | |
source | string | true | The source of the record | |
startDate | string(date-time)¦null | true | ISO-formatted first timestamp in the subset. For example: 2019-08-01T00:00:00.000000Z . |
|
status | string | true | The status of the anomaly assessment record. | |
statusDetails | string | true | The status details. |
Enumerated Values¶
Property | Value |
---|---|
anonymous | holdout |
source | [training , validation ] |
status | [noData , notSupported , completed ] |
AnomalyAssessmentRecordsResponse
{
"count": 0,
"data": [
{
"backtest": 19,
"deleteLocation": "http://example.com",
"endDate": "2019-08-24T14:15:22Z",
"latestExplanationsLocation": "http://example.com",
"modelId": "string",
"predictionThreshold": 0,
"previewLocation": "http://example.com",
"projectId": "string",
"recordId": "string",
"seriesId": "string",
"source": "training",
"startDate": "2019-08-24T14:15:22Z",
"status": "noData",
"statusDetails": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Number of items in current page. | |
data | [AnomalyAssessmentRecordResponse] | true | Anomaly assessment record. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page) | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page) |
AnomalyInsightTableData
{
"columns": [
"string"
],
"data": [
0
],
"rowId": [
0
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
columns | [string] | true | array of columns that contain columns from training dataset and anomalyScore column. |
|
data | [number] | true | array of arrays with actual data. Order in each array corresponds to order in columns array. | |
rowId | [integer] | true | index 0-based array. Each rowId corresponds to the actual row number of training data |
AnomalyInsightTableRetrieve
{
"modelId": "string",
"table": [
{
"columns": [
"string"
],
"data": [
0
],
"rowId": [
0
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
modelId | string | true | given model identifier | |
table | [AnomalyInsightTableData] | true | anomaly insights table |
AnomalyOverTimePlotsBins
{
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
endDate | string(date-time) | true | The datetime of the end of the bin (exclusive). | |
frequency | integer¦null | true | Indicates number of values averaged in bin in case of a resolution change. | |
predicted | number¦null | true | Average prediction of the model in the bin. null if there are no entries in the bin. |
|
startDate | string(date-time) | true | The datetime of the start of the bin (inclusive). |
AnomalyOverTimePlotsDataResponse
{
"bins": [
{
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"calendarEvents": [
{
"date": "2019-08-24T14:15:22Z",
"name": "string",
"seriesId": "string"
}
],
"endDate": "2019-08-24T14:15:22Z",
"resolution": "milliseconds",
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [AnomalyOverTimePlotsBins] | true | maxItems: 1000 minItems: 1 |
An array of bins for the retrieved plots. |
calendarEvents | [CalendarEvent] | true | maxItems: 1000 |
An array of calendar events for a retrieved plot. |
endDate | string(date-time) | true | The datetime of the end of the chart data (exclusive). | |
resolution | string | true | The resolution that is used for binning. | |
startDate | string(date-time) | true | The datetime of the start of the chart data (inclusive). |
Enumerated Values¶
Property | Value |
---|---|
resolution | [milliseconds , seconds , minutes , hours , days , weeks , months , quarters , years ] |
AnomalyOverTimePlotsMetadataResponse
{
"backtestMetadata": [
{
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
}
],
"backtestStatuses": [
{
"training": "completed",
"validation": "completed"
}
],
"estimatedSeriesLimit": 1,
"holdoutMetadata": {
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
},
"holdoutStatuses": {
"training": "completed",
"validation": "completed"
},
"resolutions": [
"milliseconds"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestMetadata | [DatetimeTrendPlotsBacktestMetadata] | true | maxItems: 20 minItems: 1 |
An array of metadata information for each backtest. The array index of metadata object is the backtest index. |
backtestStatuses | [AccuracyOverTimePlotsStatus] | true | maxItems: 20 minItems: 1 |
An array of status information for each backtest. The array index of status object is the backtest index. |
estimatedSeriesLimit | integer | false | minimum: 1 |
Estimated number of series that can be calculated in one request for 1 FD. |
holdoutMetadata | DatetimeTrendPlotsBacktestMetadata | true | none | |
holdoutStatuses | AccuracyOverTimePlotsStatus | true | none | |
resolutions | [string] | true | maxItems: 9 minItems: 1 |
An array of available time resolutions for which plots can be retrieved. |
AnomalyOverTimePlotsPreviewBins
{
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
endDate | string(date-time) | true | The datetime of the end of the bin (exclusive). | |
startDate | string(date-time) | true | The datetime of the start of the bin (inclusive). |
AnomalyOverTimePlotsPreviewResponse
{
"bins": [
{
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"predictionThreshold": 0,
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [AnomalyOverTimePlotsPreviewBins] | true | maxItems: 1000 |
An array of bins for the retrieved plots. |
endDate | string(date-time) | true | The datetime of the end of the chart data (exclusive). | |
predictionThreshold | number | true | maximum: 1 minimum: 0 (exclusive) |
Only bins with predictions exceeding this threshold are returned in the response. |
startDate | string(date-time) | true | The datetime of the start of the chart data (inclusive). |
AverageModelMetricsField
{
"metrics": [
{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
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"source": "validation",
"thresholds": [
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}
All average model metrics from one data source.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
metrics | [AverageModelMetricsValues] | true | maxItems: 8 minItems: 8 |
Average model metrics for the given thresholds. |
source | string | true | Chart source. | |
thresholds | [number] | true | maxItems: 100 minItems: 100 |
Threshold values for which model metrics are available. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout ] |
AverageModelMetricsValues
{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
0,
0,
0,
0,
0,
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0
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
name | string | true | Metric name. | |
numLabelsUsedInCalculation | integer | true | Number of labels that were taken into account in the calculation of metric averages | |
values | [number] | true | maxItems: 100 minItems: 100 |
Metric values at given thresholds. |
Enumerated Values¶
Property | Value |
---|---|
name | [accuracy , f1Score , falsePositiveRate , matthewsCorrelationCoefficient , negativePredictiveValue , positivePredictiveValue , trueNegativeRate , truePositiveRate ] |
BacktestStabilityPlotData
{
"backtestIndex": 0,
"partition": "string",
"score": 0,
"scoringEndDate": "2019-08-24T14:15:22Z",
"scoringStartDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestIndex | integer¦null | true | minimum: 0 |
An integer representing the index of the backtest, starting from 0. For holdout, this field will be null. |
partition | string | true | Identifier of the partition. Can either identify a specific backtest ("backtest0", "backtest1", ...) or the holdout set ("holdout"). | |
score | number¦null | true | Score for this partition. Can be null if the score is unavailable for this partition (e.g. holdout is locked or backtesting has not been run yet). | |
scoringEndDate | string(date-time) | true | End date of the subset used for scoring. | |
scoringStartDate | string(date-time) | true | Start date of the subset used for scoring. |
BacktestStabilityPlotResponse
{
"backtestPlotData": [
{
"backtestIndex": 0,
"partition": "string",
"score": 0,
"scoringEndDate": "2019-08-24T14:15:22Z",
"scoringStartDate": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"metricName": "string",
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestPlotData | [BacktestStabilityPlotData] | true | An array of objects containing the details of the scores for each partition defined for the project. | |
endDate | string(date-time) | true | End date of the project dataset. | |
metricName | string | true | Name of the metric used to compute the scores. | |
startDate | string(date-time) | true | Start date of the project dataset. |
BiasVsAccuracyInsight
{
"accuracyMetric": "AUC",
"fairnessMetric": "proportionalParity",
"fairnessThreshold": 0.8,
"models": [
{
"accuracyValue": 0,
"bp": 0,
"dsName": "string",
"fairnessValue": 1,
"modelId": "string",
"modelNumber": 0,
"modelType": "string",
"prime": true,
"samplepct": 100
}
],
"protectedFeature": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
accuracyMetric | string | false | The metric to return model accuracy scores. Defaults to the optimization metric configured in project options. | |
fairnessMetric | any | false | The fairness metric used to calculate the fairness scores. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | [string] | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
fairnessThreshold | number | true | maximum: 1 minimum: 0 |
Value of the fairness threshold, defined in project options. |
models | [BiasVsAccuracyModels] | true | An array of models of the insight. | |
protectedFeature | any | false | Name of the protected feature. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | [string] | false | none |
Enumerated Values¶
Property | Value |
---|---|
accuracyMetric | [AUC , Weighted AUC , Area Under PR Curve , Weighted Area Under PR Curve , Kolmogorov-Smirnov , Weighted Kolmogorov-Smirnov , FVE Binomial , Weighted FVE Binomial , Gini Norm , Weighted Gini Norm , LogLoss , Weighted LogLoss , Max MCC , Weighted Max MCC , Rate@Top5% , Weighted Rate@Top5% , Rate@Top10% , Weighted Rate@Top10% , Rate@TopTenth% , RMSE , Weighted RMSE ] |
anonymous | [proportionalParity , equalParity , favorableClassBalance , unfavorableClassBalance , trueUnfavorableRateParity , trueFavorableRateParity , favorablePredictiveValueParity , unfavorablePredictiveValueParity ] |
BiasVsAccuracyInsightRetrieve
{
"data": [
{
"accuracyMetric": "AUC",
"fairnessMetric": "proportionalParity",
"fairnessThreshold": 0.8,
"models": [
{
"accuracyValue": 0,
"bp": 0,
"dsName": "string",
"fairnessValue": 1,
"modelId": "string",
"modelNumber": 0,
"modelType": "string",
"prime": true,
"samplepct": 100
}
],
"protectedFeature": "string"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | [BiasVsAccuracyInsight] | true | An array of bias vs accuracy insights for the model. |
BiasVsAccuracyModels
{
"accuracyValue": 0,
"bp": 0,
"dsName": "string",
"fairnessValue": 1,
"modelId": "string",
"modelNumber": 0,
"modelType": "string",
"prime": true,
"samplepct": 100
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
accuracyValue | number | true | minimum: 0 |
The model's accuracy score. |
bp | integer | true | minimum: 0 (exclusive) |
The blueprint number of the model from the leaderboard. |
dsName | string | true | The name of the feature list used for model training. | |
fairnessValue | number¦null | true | maximum: 1 minimum: 0 |
The model's relative fairness score for the class with the lowest fairness score. In other words, the fairness score of the least privileged class. |
modelId | string | true | ID of the model. | |
modelNumber | integer | true | minimum: 0 (exclusive) |
The model number from the Leaderboard. |
modelType | string | true | The type/name of the model. | |
prime | boolean | true | Flag to indicate whether the model is a prime model. | |
samplepct | number | true | maximum: 100 minimum: 0 |
The sample size percentage of the feature list data the model was trained on. |
BinResponse
{
"avgPredicted": 0,
"endDate": "2019-08-24T14:15:22Z",
"frequency": 0,
"maxPredicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
avgPredicted | number¦null | true | Average prediction of the model in the bin. Null if there are no entries in the bin. | |
endDate | string(date-time) | true | ISO-formatted datetime of the end of the bin (exclusive). | |
frequency | integer | true | Number of the rows in the bin. | |
maxPredicted | number¦null | true | Maximum prediction of the model in the bin. Null if there are no entries in the bin. | |
startDate | string(date-time) | true | ISO-formatted datetime of the start of the bin (inclusive). |
CalendarEvent
{
"date": "2019-08-24T14:15:22Z",
"name": "string",
"seriesId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
date | string(date-time) | true | The date of the calendar event. | |
name | string | true | Name of the calendar event. | |
seriesId | string¦null | true | The series ID for the event. If this event does not specify a series ID, then this will be null , indicating that the event applies to all series. |
Categorical
{
"allData": {
"allOther": 100,
"missingRowsPercent": 100,
"perValueStatistics": [
{
"categoryLevel": "string",
"frequency": 0
}
]
},
"insightName": "categoryLevelFrequencyPercent",
"perCluster": [
{
"allOther": 100,
"clusterName": "string",
"missingRowsPercent": 100,
"perValueStatistics": [
{
"categoryLevel": "string",
"frequency": 0
}
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
allData | PerValueStatistics | true | Statistics for all data for different feature values. | |
insightName | string | true | Insight name. | |
perCluster | [PerClusterCategorical] | true | Statistic values for different feature values in this cluster. |
Enumerated Values¶
Property | Value |
---|---|
insightName | categoryLevelFrequencyPercent |
CategoricalFeature
{
"featureImpact": 0,
"featureName": "string",
"featureType": "categorical",
"insights": [
{
"allData": {
"allOther": 100,
"missingRowsPercent": 100,
"perValueStatistics": [
{
"categoryLevel": "string",
"frequency": 0
}
]
},
"insightName": "categoryLevelFrequencyPercent",
"perCluster": [
{
"allOther": 100,
"clusterName": "string",
"missingRowsPercent": 100,
"perValueStatistics": [
{
"categoryLevel": "string",
"frequency": 0
}
]
}
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureImpact | number¦null | false | Feature Impact score. | |
featureName | string | true | Feature name. | |
featureType | string | true | Feature Type. | |
insights | [Categorical] | true | A list of Cluster Insights for a feature. |
Enumerated Values¶
Property | Value |
---|---|
featureType | categorical |
ClusterInsightsPaginatedResponse
{
"count": 0,
"data": [
{
"featureImpact": 0,
"featureName": "string",
"featureType": "image",
"insights": [
{
"allData": {
"images": [
"string"
],
"percentageOfMissingImages": 100
},
"insightName": "representativeImages",
"perCluster": [
{
"clusterName": "string",
"images": [
"string"
],
"percentageOfMissingImages": 100
}
]
}
]
}
],
"isCurrentClusterInsightVersion": true,
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0,
"version": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [anyOf] | true | maxItems: 100 |
A list of features with clusters insights. |
anyOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | ImageFeature | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | GeospatialFeature | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | TextFeature | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | NumericFeature | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | CategoricalFeature | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | DocumentFeature | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
isCurrentClusterInsightVersion | boolean | true | If retrieved insights are current version. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. | |
version | integer | true | minimum: 0 |
Current version of the computed insight. |
ComputeFeatureEffectsRequest
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
dataSliceId | string | false | The ID of the data slice. | |
entityId | string | true | The ID of the entity. | |
entityType | string | true | The type of entity for which insights need to be calculated. | |
externalDatasetId | string | false | The ID of the external dataset. | |
source | string | true | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
entityType | [datarobotModel , customModel ] |
source | [validation , training , backtest_0 , backtest_1 , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 , holdout , backtest_0_training , backtest_1_training , backtest_2_training , backtest_3_training , backtest_4_training , backtest_5_training , backtest_6_training , backtest_7_training , backtest_8_training , backtest_9_training , backtest_10_training , backtest_11_training , backtest_12_training , backtest_13_training , backtest_14_training , backtest_15_training , backtest_16_training , backtest_17_training , backtest_18_training , backtest_19_training , backtest_20_training , holdout_training ] |
ComputeFeatureImpactRequest
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"rowCount": 10,
"source": "training"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
dataSliceId | string | false | The ID of the data slice. | |
entityId | string | true | The ID of the entity. | |
entityType | string | true | The type of entity for which insights need to be calculated. | |
externalDatasetId | string | false | The ID of the external dataset. | |
rowCount | integer | true | maximum: 100000 minimum: 10 |
The number of rows to use for calculating Feature Impact. |
source | string | true | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
entityType | [datarobotModel , customModel ] |
source | [training , backtest_2_training , backtest_3_training , backtest_4_training , backtest_5_training , backtest_6_training , backtest_7_training , backtest_8_training , backtest_9_training , backtest_10_training , backtest_11_training , backtest_12_training , backtest_13_training , backtest_14_training , backtest_15_training , backtest_16_training , backtest_17_training , backtest_18_training , backtest_19_training , backtest_20_training , backtest_1_training , holdout_training ] |
ComputeInsightsResponse
{
"qid": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
qid | integer¦null | true | The queue ID of the job that computes the insights request. |
ComputeLiftChartRequest
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
dataSliceId | string | false | The ID of the data slice. | |
entityId | string | true | The ID of the entity. | |
entityType | string | true | The type of entity for which insights need to be calculated. | |
externalDatasetId | string | false | The ID of the external dataset. | |
source | string | true | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
entityType | [datarobotModel , customModel ] |
source | [validation , crossValidation , holdout , externalTestSet , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
ComputeResidualsRequest
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
dataSliceId | string | false | The ID of the data slice. | |
entityId | string | true | The ID of the entity. | |
entityType | string | true | The type of entity for which insights need to be calculated. | |
externalDatasetId | string | false | The ID of the external dataset. | |
source | string | true | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
entityType | [datarobotModel , customModel ] |
source | [validation , crossValidation , holdout , externalTestSet ] |
ComputeRocCurveRequest
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
dataSliceId | string | false | The ID of the data slice. | |
entityId | string | true | The ID of the entity. | |
entityType | string | true | The type of entity for which insights need to be calculated. | |
externalDatasetId | string | false | The ID of the external dataset. | |
source | string | true | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
entityType | [datarobotModel , customModel ] |
source | [validation , crossValidation , holdout , externalTestSet , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
ComputeShapInsightsRequest
{
"dataSliceId": "string",
"entityId": "string",
"entityType": "datarobotModel",
"externalDatasetId": "string",
"quickCompute": true,
"rowCount": 0,
"source": "backtest_0"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
dataSliceId | string | false | The ID of the data slice. | |
entityId | string | true | The ID of the entity. | |
entityType | string | true | The type of entity for which insights need to be calculated. | |
externalDatasetId | string | false | The ID of the external dataset. | |
quickCompute | boolean | false | When enabled, limits the rows used from the selected source subset by default. When disabled, all rows are used. | |
rowCount | integer | false | (Deprecated) The number of rows to use for calculating SHAP Impact. | |
source | string | true | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
entityType | [datarobotModel , customModel ] |
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , externalTestSet , holdout , holdout_training , training , validation ] |
ConfusionChartClassMatrix
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actualCount | integer | true | number of times this class is seen in the validation data | |
className | string | true | name of the class | |
confusionMatrixOneVsAll | [array] | true | 2d array representing 2x2 one vs all matrix. This represents the True/False Negative/Positive rates as integer for each class. The data structure looks like: [ [ True Negative, False Positive ], [ False Negative, True Positive ] ] |
|
f1 | number | true | F1 score | |
precision | number | true | precision score | |
predictedCount | integer | true | number of times this class has been predicted for the validation data | |
recall | number | true | recall score | |
wasActualPercentages | [ActualPercentages] | true | one vs all actual percentages in a format specified below | |
wasPredictedPercentages | [PredictedPercentages] | true | one vs all predicted percentages in a format specified below |
ConfusionChartData
{
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
}
confusion chart data with the format below.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
classMetrics | [ConfusionChartClassMatrix] | true | per-class information including one vs all scores in a format specified below | |
classes | [string] | true | class labels from the dataset, union of row classes & column classes. This field is deprecated as of v2.13. The rows and columns may have different class labels when using query parameters to retrieve a slice of the matrix; please use 'rowClasses' and 'colClasses' instead. | |
colClasses | [string] | true | class labels on columns of confusion matrix | |
confusionMatrix | [array] | true | 2d array of ints representing confusion matrix, aligned with rowClasses and 'colClasses'array. For confusionMatrix[A][B] we can get an integer that represents the number of times 'if class with index A was correct we have class with index B predicted' (if the orientation is 'actual'). |
|
rowClasses | [string] | true | class labels on rows of confusion matrix |
ConfusionChartForDatasetsListResponse
{
"count": 0,
"data": [
{
"columns": [
0
],
"data": {
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
},
"globalMetrics": {
"f1": 0,
"precision": 0,
"recall": 0
},
"numberOfClasses": 0,
"rows": [
0
],
"source": "validation",
"totalMatrixSum": 0
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Number of results returned on this page. | |
data | [ModelConfusionChartRetrieveResponse] | true | Confusion chart data with the in the same format as the response from GET /api/v2/projects/{projectId}/models/{modelId}/confusionCharts/{source}/ with additional totalCount field. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | Total count of confusion charts for model. |
ConfusionChartRetrieveForDatasets
{
"columns": [
0
],
"data": {
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
},
"datasetId": "string",
"numberOfClasses": 0,
"rows": [
0
],
"totalMatrixSum": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
columns | [integer] | true | [colStart, colEnd] column dimension of confusion matrix in response | |
data | ConfusionChartData | true | confusion chart data with the format below. | |
datasetId | string | true | The datasetId to retrieve a Confusion chart from. | |
numberOfClasses | integer | true | count of classes in full confusion matrix. | |
rows | [integer] | true | [rowStart, rowEnd] row dimension of confusion matrix in response | |
totalMatrixSum | integer | true | sum of all values in full confusion matrix |
ConfusionChartRetrieveMetadataForDatasets
{
"classNames": [
"string"
],
"datasetId": "string",
"modelId": "string",
"projectId": "string",
"relevantClassesPositions": [
[
0
]
],
"totalMatrixSum": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
classNames | [string] | true | list of all class names in the full confusion matrix, sorted by the orderBy parameter. |
|
datasetId | string | true | The dataset to retrieve a Confusion chart from. | |
modelId | string | true | The model to retrieve a Confusion chart from. | |
projectId | string | true | The project to retrieve a Confusion chart from. | |
relevantClassesPositions | [array] | true | Matrix to highlight important cell blocks in the confusion chart. Intended to represent a thumbnail view, where the relevantClassesPositions array has a 1 in thumbnail cells that are of interest, and 0 otherwise. The dimensions of the implied thumbnail will not match those of the confusion matrix, e.g. a twenty-class confusion matrix may have a 2x2 thumbnail. | |
totalMatrixSum | integer | true | Sum of all values in the full confusion matrix (equal to the number of points considered). |
CreateShapMatrixPayload
{
"datasetId": "string",
"modelId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
datasetId | string | true | The dataset ID. | |
modelId | string | true | The model ID. |
CrossClassAccuracy
{
"feature": "string",
"modelId": "string",
"perClassAccuracyScores": [
{
"className": "string",
"metrics": [
{
"metric": "AUC",
"value": 1
}
]
}
],
"predictionThreshold": 1
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
feature | string | true | The name of the categorical feature. | |
modelId | string | true | ID of the model for the cross-class accuracy scores. | |
perClassAccuracyScores | [PerClassAccuracy] | true | An array of metric scores for each class of the feature. | |
predictionThreshold | number | true | maximum: 1 minimum: 0 |
Value of the prediction threshold for the model. |
CrossClassAccuracyCreateResponse
{
"statusId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
statusId | string | true | The ID of the status object. |
CrossClassAccuracyList
{
"count": 0,
"data": [
{
"feature": "string",
"modelId": "string",
"perClassAccuracyScores": [
{
"className": "string",
"metrics": [
{
"metric": "AUC",
"value": 1
}
]
}
],
"predictionThreshold": 1
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [CrossClassAccuracy] | true | An array of cross-class accuracy scores for the model. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
DataDisparityCreatePayload
{
"comparedClassNames": [
"string",
"string"
],
"feature": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
comparedClassNames | [string] | true | maxItems: 2 minItems: 2 |
An array of classes to calculate data disparity for. |
feature | string | true | Feature for which insight is computed. |
DataDisparityCreateResponse
{
"statusId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
statusId | string | true | The ID of the status object. |
DataDisparityInsights
{
"features": [
{
"detailsHistogram": [
{
"bars": [
{
"label": "string",
"value": 0
}
],
"bin": "string"
}
],
"disparityScore": 0,
"featureImpact": 0,
"name": "string",
"status": "Healthy"
}
],
"metric": "string",
"protectedFeature": "string",
"values": [
{
"count": 0,
"label": "string"
}
]
}
Computed data disparity insights if available.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
features | [AnalyzedFeature] | false | A mapping of the feature name to the corresponding values on the graph. | |
metric | string | false | Metric used to calculate the impact of a feature on data disparity. | |
protectedFeature | string | false | Feature for which insights were computed. | |
values | [FeatureCounts] | false | Class count details for each class being compared. |
DataDisparityRetrieveResponse
{
"count": 0,
"data": {
"features": [
{
"detailsHistogram": [
{
"bars": [
{
"label": "string",
"value": 0
}
],
"bin": "string"
}
],
"disparityScore": 0,
"featureImpact": 0,
"name": "string",
"status": "Healthy"
}
],
"metric": "string",
"protectedFeature": "string",
"values": [
{
"count": 0,
"label": "string"
}
]
},
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | DataDisparityInsights | true | Computed data disparity insights if available. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
DataPointResponse
{
"prediction": 0,
"shapExplanation": [
{
"feature": "string",
"featureValue": "string",
"strength": 0
}
],
"timestamp": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
prediction | number | true | The output of the model for this row. | |
shapExplanation | [ShapExplanationResponse]¦null | true | Either null or an array of up to 10 ShapleyFeatureContribution objects. Only rows with the highest anomaly scores have Shapley explanations calculated. |
|
timestamp | string(date-time) | true | ISO-formatted timestamp for the row. |
DataSliceComputeSubsetSizeRequest
{
"externalDatasetId": "string",
"modelId": "string",
"projectId": "string",
"source": "backtest_0"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
externalDatasetId | string¦null | false | The external dataset ID to use when calculating the size of a slice. Use this parameter only when the source is 'externalTestSet'. | |
modelId | string¦null | false | The model ID whose training dataset should be sliced. Use this parameter only when the source is 'training'. | |
projectId | string | true | The project ID. | |
source | string | true | The source of data to use to calculate the size. |
Enumerated Values¶
Property | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , crossValidation , externalTestSet , holdout , holdout_training , training , validation ] |
DataSliceIndividualResponse
{
"filters": [
{
"operand": "string",
"operator": "eq",
"values": [
"string"
]
}
],
"id": "string",
"name": "string",
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
filters | [FilterDataSlices] | true | maxItems: 3 minItems: 1 |
List of filters the data slice is composed of. |
id | string | true | ID of the data slice. | |
name | string | true | maxLength: 500 minLength: 1 minLength: 1 |
User provided name for the data slice. |
projectId | string | true | The project ID. |
DataSliceMessage
{
"additionalInfo": "string",
"description": "string",
"level": "CRITICAL"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
additionalInfo | string | true | Additional details about this message. | |
description | string | true | Short summary description about this message. | |
level | string | true | Message level. |
Enumerated Values¶
Property | Value |
---|---|
level | [CRITICAL , INFORMATIONAL , WARNING ] |
DataSliceRetrieveSubsetSizeResponse
{
"dataSliceId": "string",
"externalDatasetId": "string",
"messages": [
{
"additionalInfo": "string",
"description": "string",
"level": "CRITICAL"
}
],
"modelId": "string",
"projectId": "string",
"sliceSize": 0,
"source": "backtest_0"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
dataSliceId | string | true | ID of the data slice. | |
externalDatasetId | string¦null | false | The external dataset ID to use when calculating the size of a slice. Use this parameter only when the source is 'externalTestSet'. | |
messages | [DataSliceMessage] | true | maxItems: 100 |
List of user-relevant messages related to a Data Slice. |
modelId | string¦null | false | The model ID whose training dataset should be sliced. Use this parameter only when the source is 'training'. | |
projectId | string | true | The project ID. | |
sliceSize | integer | true | minimum: 0 |
Number of rows in the slice for the given source. |
source | string | true | The source of data to use to calculate the size. |
Enumerated Values¶
Property | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , crossValidation , externalTestSet , holdout , holdout_training , training , validation ] |
DataSlicesBulkDeleteRequest
{
"ids": [
"string"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
ids | [string] | true | maxItems: 20 minItems: 1 |
List of data slices to remove. |
DataSlicesCreationRequest
{
"filters": [
{
"operand": "string",
"operator": "eq",
"values": [
"string"
]
}
],
"name": "string",
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
filters | [FilterDataSlices] | true | maxItems: 3 minItems: 1 |
List of filters the data slice is composed of. |
name | string | true | maxLength: 500 minLength: 1 minLength: 1 |
User provided name for the data slice. |
projectId | string | true | The project ID. |
DataSlicesListAllSlicesResponse
{
"count": 0,
"data": [
{
"filters": [
{
"operand": "string",
"operator": "eq",
"values": [
"string"
]
}
],
"id": "string",
"name": "string",
"projectId": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [DataSliceIndividualResponse] | true | maxItems: 100 |
List of paginated Data Slices. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
DatetimeTrendPlotsBacktestMetadata
{
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
training | DatetimeTrendPlotsMetadataStartEndDates | true | Start and end dates for the backtest/holdout training. | |
validation | DatetimeTrendPlotsMetadataStartEndDates | true | Start and end dates for the backtest/holdout training. |
DatetimeTrendPlotsCreate
{
"backtest": 0,
"forecastDistanceEnd": 0,
"forecastDistanceStart": 0,
"fullAverage": false,
"seriesIds": [
"string"
],
"source": "training"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtest | any | false | Compute plots for a specific backtest (use the backtest index starting from zero) or holdout . If not specified the first backtest (backtest index 0) will be used. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | maximum: 19 minimum: 0 |
none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
forecastDistanceEnd | integer | false | minimum: 0 |
The end of forecast distance range (forecast window) to compute. If not specified, the last forecast distance for this project will be used. Forecast distance specifies the number of time steps between the predicted point and the origin point. Only available for time series supervised projects. |
forecastDistanceStart | integer | false | minimum: 0 |
The start of forecast distance range (forecast window) to compute. If not specified, the first forecast distance for this project will be used. Forecast distance specifies the number of time steps between the predicted point and the origin point. Only available for time series supervised projects. |
fullAverage | boolean | false | Whether to compute an average plot for all series. Only available for time series multiseries projects. | |
seriesIds | [string] | false | maxItems: 1000 minItems: 1 |
Only available for time series multiseries projects. Each element should be a name of a single series in a multiseries project. It is possible to compute a maximum of 1000 series per one request. If not specified the first 1000 series in alphabetical order will be computed. It is not possible to specify fullAverage: true while also setting seriesIds . This parameter can only be specified after first 1000 series in alphabetical order are computed. |
source | string | false | The source of the data for the backtest/holdout. |
Enumerated Values¶
Property | Value |
---|---|
anonymous | holdout |
source | [training , validation ] |
DatetimeTrendPlotsMetadataStartEndDates
{
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
Start and end dates for the backtest/holdout training.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
endDate | string(date-time)¦null | true | The datetime of the end of the chart data (exclusive). Null if chart data is not computed. | |
startDate | string(date-time)¦null | true | The datetime of the start of the chart data (inclusive). Null if chart data is not computed. |
DatetimeTrendPlotsPreviewBins
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actual | number¦null | true | Average actual value of the target in the bin. null if there are no entries in the bin. |
|
endDate | string(date-time) | true | The datetime of the end of the bin (exclusive). | |
predicted | number¦null | true | Average prediction of the model in the bin. null if there are no entries in the bin. |
|
startDate | string(date-time) | true | The datetime of the start of the bin (inclusive). |
DatetimeTrendPlotsPreviewResponse
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"predicted": 0,
"startDate": "2019-08-24T14:15:22Z"
}
],
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [DatetimeTrendPlotsPreviewBins] | true | maxItems: 1000 minItems: 1 |
An array of bins for the retrieved plots. |
endDate | string(date-time) | true | The datetime of the end of the chart data (exclusive). | |
startDate | string(date-time) | true | The datetime of the start of the chart data (inclusive). |
DatetimeTrendPlotsResponse
{
"message": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
message | string | false | Any extended message to include about the result. For example, if a job is submitted that is a duplicate of a job that has already been added to the queue, the message will mention that no new job can be created. |
DocumentFeature
{
"featureImpact": 0,
"featureName": "string",
"featureType": "document",
"insights": [
{
"allData": {
"missingRowsPercent": 100,
"perValueStatistics": [
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
]
},
"insightName": "importantNgrams",
"perCluster": [
{
"clusterName": "string",
"missingRowsPercent": 100,
"perValueStatistics": [
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
]
}
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureImpact | number¦null | false | Feature Impact score. | |
featureName | string | true | Feature name. | |
featureType | string | true | Feature Type. | |
insights | [Text] | true | A list of Cluster Insights for a feature. |
Enumerated Values¶
Property | Value |
---|---|
featureType | document |
Empty
{}
Properties¶
None
ExternalScoresCreate
{
"actualValueColumn": "string",
"datasetId": "string",
"modelId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actualValueColumn | string | false | Actual value column name that contains actual values to be used for computing scores and insights for unsupervised projects only. This value can be set once for a dataset and cannot be changed. | |
datasetId | string | true | The dataset to compute predictions for - must have previously been uploaded. | |
modelId | string | true | The model to use to make predictions. |
ExternalScoresListData
{
"actualValueColumn": "string",
"datasetId": "string",
"modelId": "string",
"projectId": "string",
"scores": [
{
"label": "string",
"value": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actualValueColumn | string | true | The name of the column with actuals that was used to calculate the scores. | |
datasetId | string | true | The datasetId the data comes from. | |
modelId | string | true | The modelId for the scores. | |
projectId | string | true | The projectId for the scores. | |
scores | [ExternalScoresListDataScore] | true | A json array of the computed scores. |
ExternalScoresListDataScore
{
"label": "string",
"value": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
label | string | true | The metric name, which was used to compute the score. | |
value | number | true | The score value. |
ExternalScoresListResponse
{
"count": 0,
"data": [
{
"actualValueColumn": "string",
"datasetId": "string",
"modelId": "string",
"projectId": "string",
"scores": [
{
"label": "string",
"value": 0
}
]
}
],
"next": "string",
"previous": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Number of items returned on this page. | |
data | [ExternalScoresListData] | true | The list of objects is containing following data. | |
next | string¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string¦null | true | URL pointing to the previous page (if null, there is no previous page). |
FairnessInsight
{
"fairnessMetric": "proportionalParity",
"fairnessThreshold": 0.8,
"modelId": "string",
"perClassFairness": [
{
"absoluteValue": 0,
"className": "string",
"entriesCount": 0,
"isStatisticallySignificant": true,
"value": 1
}
],
"predictionThreshold": 1,
"protectedFeature": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
fairnessMetric | string | true | The fairness metric used to calculate the fairness scores. | |
fairnessThreshold | number | true | maximum: 1 minimum: 0 |
Value of the fairness threshold, defined in project options. |
modelId | string | true | ID of the model fairness was measured for. | |
perClassFairness | [PerClassFairness] | true | An array of calculated fairness scores for each protected feature class. | |
predictionThreshold | number | false | maximum: 1 minimum: 0 |
Model's prediction threshold used when insight was calculated. null if prediction threshold is not required for the fairness metric calculations. |
protectedFeature | string | true | Name of the protected feature the fairness calculation is made for. |
Enumerated Values¶
Property | Value |
---|---|
fairnessMetric | [proportionalParity , equalParity , favorableClassBalance , unfavorableClassBalance , trueUnfavorableRateParity , trueFavorableRateParity , favorablePredictiveValueParity , unfavorablePredictiveValueParity ] |
FairnessInsightsListResponse
{
"count": 0,
"data": [
{
"fairnessMetric": "proportionalParity",
"fairnessThreshold": 0.8,
"modelId": "string",
"perClassFairness": [
{
"absoluteValue": 0,
"className": "string",
"entriesCount": 0,
"isStatisticallySignificant": true,
"value": 1
}
],
"predictionThreshold": 1,
"protectedFeature": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [FairnessInsight] | true | An array of fairness insights for the model. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
FairnessInsightsStartCalculationPayload
{
"fairnessMetricsSet": "proportionalParity"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
fairnessMetricsSet | string | false | Metric to use for calculating fairness. Can be one of proportionalParity , equalParity , predictionBalance , trueFavorableAndUnfavorableRateParity or FavorableAndUnfavorablePredictiveValueParity . Used and required only if Bias & Fairness in AutoML feature is enabled. |
Enumerated Values¶
Property | Value |
---|---|
fairnessMetricsSet | [proportionalParity , equalParity , predictionBalance , trueFavorableAndUnfavorableRateParity , favorableAndUnfavorablePredictiveValueParity ] |
FairnessInsightsStartCalculationResponse
{
"statusId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
statusId | string | true | The ID of the status object. |
FeatureAssociationCreatePayload
{
"featurelistId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featurelistId | string | true | A featurelist ID to calculate feature association matrix. |
FeatureAssociationDetailsRetrieveControllerResponse
{
"chartType": "string",
"features": [
"string"
],
"types": [
"CATEGORICAL"
],
"values": [
[
"string"
]
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
chartType | string | true | Which type of plotting the pair of features gets in the UI, e.g. SCATTER |
|
features | [string] | true | The name of feature1 and feature2 . |
|
types | [string] | true | The type of feature1 and feature2 . Possible values: CATEGORICAL , NUMERIC . |
|
values | [array] | true | The data triplets for pairwise plotting. |
anyOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | number | false | none |
FeatureAssociationList
{
"featurelistId": "string",
"hasFam": true,
"title": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featurelistId | string | true | The featurelist Id. | |
hasFam | boolean | true | Whether Feature Association Matrix is calculated for featurelist. | |
title | string | true | The name of featurelist. |
FeatureAssociationListControllerResponse
{
"featurelists": [
{
"featurelistId": "string",
"hasFam": true,
"title": "string"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featurelists | [FeatureAssociationList] | true | List all featurelists with feature association matrix availability flags. |
FeatureAssociationRetrieveControllerResponse
{
"features": [
{
"alphabeticSortIndex": 0,
"clusterId": 0,
"clusterName": "string",
"clusterSortIndex": 0,
"feature": "string",
"importanceSortIndex": 0,
"strengthSortIndex": 0
}
],
"strengths": [
{
"feature1": "string",
"feature2": "string",
"statistic": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
features | [FeatureAssociationRetrieveFeatures] | true | Metadata for each feature and where it goes in the matrix as structured below. | |
strengths | [FeatureAssociationRetrieveStrengths] | true | Pairwise statistics for the available features as structured below. |
FeatureAssociationRetrieveFeatures
{
"alphabeticSortIndex": 0,
"clusterId": 0,
"clusterName": "string",
"clusterSortIndex": 0,
"feature": "string",
"importanceSortIndex": 0,
"strengthSortIndex": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
alphabeticSortIndex | integer | true | A number representing the alphabetical order of this feature compared to the other features in this dataset. | |
clusterId | integer¦null | true | ID of the cluster this feature belongs to. | |
clusterName | string | false | Name of feature cluster. | |
clusterSortIndex | integer | true | A number representing the ordering of the feature across all feature clusters. Features in the same cluster always have adjacent indices. | |
feature | string | true | Name of the feature. | |
importanceSortIndex | integer | true | A number ranking the importance of this feature compared to the other features in this dataset. | |
strengthSortIndex | integer | true | A number ranking the strength of this feature compared to the other features in this dataset. |
FeatureAssociationRetrieveStrengths
{
"feature1": "string",
"feature2": "string",
"statistic": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
feature1 | string | true | The name of the first feature. | |
feature2 | string | true | The name of the second feature. | |
statistic | number¦null | true | Feature association statistics for feature1 and feature2 . For features with no pairwise statistics available the value is null . |
FeatureCounts
{
"count": 0,
"label": "string"
}
Number of occurrences of each class being compared.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Number of times the class was encountered. | |
label | string | true | Name of the class. |
FeatureEffectCreate
{
"rowCount": 10
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
rowCount | integer¦null | false | maximum: 100000 minimum: 10 |
The number of rows from dataset to use for Feature Impact calculation. |
FeatureEffects
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureImpactScore | number | true | Feature impact score. | |
featureName | string | true | Name of the feature. | |
featureType | string | true | Feature type, either numeric or categorical. | |
isBinnable | boolean | true | Whether values can be grouped into bins. | |
isScalable | boolean¦null | true | Whether numeric feature values can be reported on a log scale. | |
partialDependence | PartialDependence | false | Partial dependence results. Can be missing if no data for the feature was qualified to generate the insight. | |
predictedVsActual | PredictedVsActual | false | Predicted versus actual results. Can be missing if no data for the feature was qualified to generate the insight. | |
weightLabel | string¦null | true | Weight label if weight was configured for the project. |
FeatureEffectsCreateDatetime
{
"backtestIndex": "string",
"rowCount": 10
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestIndex | string | true | The backtest index. For example: 0 , 1 , ..., 20 , holdout , startstop . |
|
rowCount | integer¦null | false | maximum: 100000 minimum: 10 |
The number of rows from dataset to use for Feature Impact calculation. |
FeatureEffectsDatetimeResponse
{
"backtestIndex": "string",
"featureEffects": [
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
],
"modelId": "string",
"projectId": "string",
"source": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestIndex | string | true | The backtest index. For example: 0 , 1 , ..., 20 , holdout , startstop . |
|
featureEffects | [FeatureEffects] | true | Feature Effects computational results for each feature. | |
modelId | string | true | The model ID | |
projectId | string | true | The project ID | |
source | string | true | Models data source. |
FeatureEffectsInsightResponse
{
"featureEffects": [
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
]
}
Feature effects data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureEffects | [FeatureEffects] | true | Feature Effects computational results for each feature. |
FeatureEffectsResponse
{
"featureEffects": [
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
],
"modelId": "string",
"projectId": "string",
"source": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureEffects | [FeatureEffects] | true | Feature Effects computational results for each feature. | |
modelId | string | true | The model ID | |
projectId | string | true | The project ID | |
source | string | true | Models data source. |
FeatureImpactCreatePayload
{
"rowCount": 10
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
rowCount | integer | false | maximum: 100000 minimum: 10 |
The sample size to use for Feature Impact computation. It is possible to re-compute Feature Impact with a different row count. |
FeatureImpactInsightResponse
{
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
],
"ranRedundancyDetection": true,
"rowCount": 0
}
Feature impact data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureImpacts | [FeatureImpactItem] | true | maxItems: 1000 |
A list which contains feature impact scores for each feature used by a model. If the model has more than 1000 features, the most important 1000 features are returned. |
ranRedundancyDetection | boolean | true | Indicates whether redundant feature identification was run while calculating this feature impact. | |
rowCount | integer¦null | true | The number of rows that was used to calculate feature impact. For the feature impact calculated with the default logic, without specifying the rowCount , we return null here. |
FeatureImpactItem
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureName | string | true | The name of the feature. | |
impactNormalized | number | true | maximum: 1 |
The same as impactUnnormalized , but normalized such that the highest value is 1 . |
impactUnnormalized | number | true | How much worse the error metric score is when making predictions on modified data. | |
parentFeatureName | string¦null | false | The name of the parent feature. | |
redundantWith | string¦null | true | Name of feature that has the highest correlation with this feature. |
FilterDataSlices
{
"operand": "string",
"operator": "eq",
"values": [
"string"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
operand | string | true | Feature to apply operation to. | |
operator | string | true | Operator to apply to the named operand in the dataset. The operator 'eq' mean 'equals the single specified value'. The operator 'in' means 'is one of a list of allowed values.' | |
values | [anyOf] | true | maxItems: 1000 minItems: 1 |
Values to filter the operand by with the given operator. |
anyOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | number | false | none |
Enumerated Values¶
Property | Value |
---|---|
operator | [eq , in , < , > , between , notBetween ] |
ForecastDistancePlotDataEntryResponse
{
"backtestingScore": 0,
"forecastDistance": 0,
"holdoutScore": 0,
"validationScore": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestingScore | number¦null | true | Backtesting score for this forecast distance. If backtesting has not been run for this model, this score will be null . |
|
forecastDistance | integer | true | The number of time units the scored rows are away from the forecast point. | |
holdoutScore | number¦null | true | Holdout set score for this forecast distance. If holdout is locked for the project, this score will be null . |
|
validationScore | number | true | Validation set score for this forecast distance. |
ForecastDistanceStabilityPlotResponse
{
"endDate": "2019-08-24T14:15:22Z",
"forecastDistancePlotData": [
{
"backtestingScore": 0,
"forecastDistance": 0,
"holdoutScore": 0,
"validationScore": 0
}
],
"metricName": "string",
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
endDate | string(date-time) | true | ISO-formatted start date of the project dataset. | |
forecastDistancePlotData | [ForecastDistancePlotDataEntryResponse] | true | An array of objects containing the details of the scores for each forecast distance. | |
metricName | string | true | Name of the metric used to compute the scores. | |
startDate | string(date-time) | true | ISO-formatted start date of the project dataset. |
ForecastVsActualPlotsBins
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"error": 0,
"forecasts": [
0
],
"frequency": 0,
"normalizedError": 1,
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actual | number¦null | true | Average actual value of the target in the bin. null if there are no entries in the bin. |
|
endDate | string(date-time) | true | The datetime of the end of the bin (exclusive). | |
error | number¦null | true | minimum: 0 |
Average absolute residual value of the bin. null if there are no entries in the bin. |
forecasts | [number] | true | maxItems: 100 |
An array of average forecasts for the model for each forecast distance. Empty if there are no forecasts in the bin. Each index in the forecasts array maps to forecastDistances array index. |
frequency | integer¦null | true | Indicates number of values averaged in bin in case of a resolution change. | |
normalizedError | number¦null | true | maximum: 1 minimum: 0 |
Normalized average absolute residual value of the bin. null if there are no entries in the bin. |
startDate | string(date-time) | true | The datetime of the start of the bin (inclusive). |
ForecastVsActualPlotsDataResponse
{
"bins": [
{
"actual": 0,
"endDate": "2019-08-24T14:15:22Z",
"error": 0,
"forecasts": [
0
],
"frequency": 0,
"normalizedError": 1,
"startDate": "2019-08-24T14:15:22Z"
}
],
"calendarEvents": [
{
"date": "2019-08-24T14:15:22Z",
"name": "string",
"seriesId": "string"
}
],
"endDate": "2019-08-24T14:15:22Z",
"forecastDistances": [
1
],
"resolution": "milliseconds",
"startDate": "2019-08-24T14:15:22Z"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [ForecastVsActualPlotsBins] | true | maxItems: 1000 minItems: 1 |
An array of bins for the retrieved plots. |
calendarEvents | [CalendarEvent] | true | maxItems: 1000 |
An array of calendar events for a retrieved plot. |
endDate | string(date-time) | true | The datetime of the end of the chart data (exclusive). | |
forecastDistances | [integer] | true | maxItems: 100 minItems: 1 |
An array of forecast distances. Forecast distance specifies the number of time steps between the predicted point and the origin point. |
resolution | string | true | The resolution that is used for binning. | |
startDate | string(date-time) | true | The datetime of the start of the chart data (inclusive). |
Enumerated Values¶
Property | Value |
---|---|
resolution | [milliseconds , seconds , minutes , hours , days , weeks , months , quarters , years ] |
ForecastVsActualPlotsForecastDistancesStatus
{
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
}
Status for backtest/holdout training.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
completed | [integer] | false | maxItems: 1000 minItems: 1 |
An array of available forecast distances for the completed status. If there are no forecast distances for this status, it will not appear in the response. |
errored | [integer] | false | maxItems: 1000 minItems: 1 |
An array of available forecast distances for the errored status. If there are no forecast distances for this status, it will not appear in the response. |
inProgress | [integer] | false | maxItems: 1000 minItems: 1 |
An array of available forecast distances for the inProgress status. If there are no forecast distances for this status, it will not appear in the response. |
insufficientData | [integer] | false | maxItems: 1000 minItems: 1 |
An array of available forecast distances for the insufficientData status. If there are no forecast distances for this status, it will not appear in the response. |
notCompleted | [integer] | false | maxItems: 1000 minItems: 1 |
An array of available forecast distances for the notCompleted status. If there are no forecast distances for this status, it will not appear in the response. |
ForecastVsActualPlotsMetadataResponse
{
"backtestMetadata": [
{
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
}
],
"backtestStatuses": [
{
"training": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
},
"validation": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
}
}
],
"estimatedSeriesLimit": 1,
"holdoutMetadata": {
"training": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
},
"validation": {
"endDate": "2019-08-24T14:15:22Z",
"startDate": "2019-08-24T14:15:22Z"
}
},
"holdoutStatuses": {
"training": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
},
"validation": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
}
},
"resolutions": [
"milliseconds"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestMetadata | [DatetimeTrendPlotsBacktestMetadata] | true | maxItems: 20 minItems: 1 |
An array of metadata information for each backtest. The array index of metadata object is the backtest index. |
backtestStatuses | [ForecastVsActualPlotsStatus] | true | maxItems: 20 minItems: 1 |
An array of status information for each backtest. The array index of status object is the backtest index. |
estimatedSeriesLimit | integer | false | minimum: 1 |
Estimated number of series that can be calculated in one request for 1 FD. |
holdoutMetadata | DatetimeTrendPlotsBacktestMetadata | true | none | |
holdoutStatuses | ForecastVsActualPlotsStatus | true | none | |
resolutions | [string] | true | maxItems: 9 minItems: 1 |
An array of available time resolutions for which plots can be retrieved. |
ForecastVsActualPlotsStatus
{
"training": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
},
"validation": {
"completed": [
1
],
"errored": [
1
],
"inProgress": [
1
],
"insufficientData": [
1
],
"notCompleted": [
1
]
}
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
training | ForecastVsActualPlotsForecastDistancesStatus | true | Status for backtest/holdout training. | |
validation | ForecastVsActualPlotsForecastDistancesStatus | true | Status for backtest/holdout training. |
FrequentValueData
{
"count": 0,
"dataQuality": "string",
"target": 0,
"value": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Count of specified frequent value in the sample, weighted by exposure or weights | |
dataQuality | string | true | Any data quality issue associated with this particularvalue of the feature. Possible data quality types include 'excess_zero', 'inlier', 'disguised_missing_value', and 'no_issues_found' and the relevant statistics. | |
target | number¦null | true | Average target value for the specified frequent value if the target is binary or numeric. With weights or exposure, this becomes a weighted average. If the target is not set, it returns None. | |
value | any | true | Specified frequent value, either a float or a string, like =All Others+ |
anyOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | number | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
FrequentValuesResponse
{
"frequentValues": [
{
"count": 0,
"dataQuality": "string",
"target": 0,
"value": 0
}
],
"name": "string",
"numRows": 0,
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
frequentValues | [FrequentValueData] | true | List of frequent value and data quality information | |
name | string | true | Name of the feature | |
numRows | integer | true | Number of rows in the sample used to determine frequent values | |
projectId | string | true | Project Id |
GeoFeaturePlotData
{
"aggregation": "grid",
"bbox": {},
"features": [
{
"geometry": {
"coordinates": [
{}
],
"type": "Point"
},
"properties": {
"count": 0
},
"type": "string"
}
],
"summary": {
"maxCount": 0,
"minCount": 0,
"totalCount": 0
},
"type": "string",
"valueAggregation": "geometry"
}
Geo feature plot data
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
aggregation | string | true | Type of geo aggregation. | |
bbox | object | true | Bounding box of feature map. | |
features | [GeoFeaturePlotFeature] | true | Location features over map | |
summary | GeoFeaturePlotSummary | true | Summary of feature map. | |
type | string | true | GeoJSON FeatureCollection. | |
valueAggregation | string | true | Type of feature aggregation. |
Enumerated Values¶
Property | Value |
---|---|
aggregation | [grid , unique ] |
valueAggregation | geometry |
GeoFeaturePlotFeature
{
"geometry": {
"coordinates": [
{}
],
"type": "Point"
},
"properties": {
"count": 0
},
"type": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
geometry | GeoJSON | true | Geometry. | |
properties | GeoFeaturePlotFeatureProperties | true | Properties of location features. | |
type | string | true | With a fixed value of 'Feature'. |
GeoFeaturePlotFeatureProperties
{
"count": 0
}
Properties of location features.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Total num of samples located within this geometry. |
GeoFeaturePlotSummary
{
"maxCount": 0,
"minCount": 0,
"totalCount": 0
}
Summary of feature map.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
maxCount | integer | true | Max num of samples located within one geometry. | |
minCount | integer | true | Min num of samples located within one geometry. | |
totalCount | integer | true | Total num of samples across all geometry objects. |
GeoJSON
{
"coordinates": [
{}
],
"type": "Point"
}
Geometry.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
coordinates | [object] | true | Coordinate representative of a geometry. | |
type | string | true | Type of geometry. |
Enumerated Values¶
Property | Value |
---|---|
type | [Point , LineString , Polygon ] |
GeometryFeaturePLotCreatePayload
{
"feature": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
feature | string | true | Name of a location feature from the dataset to plot on map. |
GeometryFeaturePlotRetrieveResponse
{
"feature": "string",
"plotData": {
"aggregation": "grid",
"bbox": {},
"features": [
{
"geometry": {
"coordinates": [
{}
],
"type": "Point"
},
"properties": {
"count": 0
},
"type": "string"
}
],
"summary": {
"maxCount": 0,
"minCount": 0,
"totalCount": 0
},
"type": "string",
"valueAggregation": "geometry"
},
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
feature | string | true | Name of location feature to plot on map. | |
plotData | GeoFeaturePlotData | true | Geo feature plot data | |
projectId | string | true | The project to select a location feature from. |
GeospatialFeature
{
"featureImpact": 0,
"featureName": "string",
"featureType": "geospatialPoint",
"insights": [
{
"insightName": "representativeLocations",
"perCluster": [
{
"clusterName": "string",
"representativeLocations": [
[
-180
]
]
}
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureImpact | number¦null | false | Feature Impact score. | |
featureName | string | true | Feature name. | |
featureType | string | true | Feature type. | |
insights | [GeospatialInsights] | true | A list of Cluster Insights for a geospatial centroid or point feature. |
Enumerated Values¶
Property | Value |
---|---|
featureType | geospatialPoint |
GeospatialInsights
{
"insightName": "representativeLocations",
"perCluster": [
{
"clusterName": "string",
"representativeLocations": [
[
-180
]
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
insightName | string | true | Insight name. | |
perCluster | [PerClusterGeospatial] | true | Statistic for different feature values in this cluster. |
Enumerated Values¶
Property | Value |
---|---|
insightName | representativeLocations |
GlobalMetrics
{
"f1": 0,
"precision": 0,
"recall": 0
}
average metrics across all classes
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
f1 | number | true | Average F1 score | |
precision | number | true | Average precision score | |
recall | number | true | Avergae recall score |
Histogram
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
intervalEnd | number | true | The end of the interval. | |
intervalStart | number | true | The start of the interval. | |
occurrences | integer | true | The number of times the predicted value fits within that interval. |
HistogramBarsDetails
{
"label": "string",
"value": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
label | string | true | Name of the class. | |
value | number | true | Ratio of occurrence of the class. |
HistogramDetails
{
"bars": [
{
"label": "string",
"value": 0
}
],
"bin": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bars | [HistogramBarsDetails] | true | Class details for the histogram chart | |
bin | any | true | Label for the bin grouping |
anyOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | none |
ImageFeature
{
"featureImpact": 0,
"featureName": "string",
"featureType": "image",
"insights": [
{
"allData": {
"images": [
"string"
],
"percentageOfMissingImages": 100
},
"insightName": "representativeImages",
"perCluster": [
{
"clusterName": "string",
"images": [
"string"
],
"percentageOfMissingImages": 100
}
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureImpact | number¦null | false | Feature Impact score. | |
featureName | string | true | Feature name. | |
featureType | string | true | Feature Type. | |
insights | [ImageInsights] | true | A list of Cluster Insights for an image feature. |
Enumerated Values¶
Property | Value |
---|---|
featureType | image |
ImageInsights
{
"allData": {
"images": [
"string"
],
"percentageOfMissingImages": 100
},
"insightName": "representativeImages",
"perCluster": [
{
"clusterName": "string",
"images": [
"string"
],
"percentageOfMissingImages": 100
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
allData | AllDataImage | false | Statistics for all data for different feature values. | |
insightName | string | true | Insight name. | |
perCluster | [PerClusterImage] | true | Statistic values for different feature values in this cluster. |
Enumerated Values¶
Property | Value |
---|---|
insightName | representativeImages |
LabelRelevancePlot
{
"labelRelevance": 1,
"rowCount": 0,
"rowPct": 100
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
labelRelevance | integer | true | maximum: 1 minimum: 0 |
Label relevance value. |
rowCount | integer | true | minimum: 0 |
Number of rows for which the label has the given relevance. |
rowPct | number | true | maximum: 100 minimum: 0 |
Percentage of rows for which the label has the given relevance. |
LabelwiseLiftChart
{
"labelBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"label": "string"
}
],
"labels": [
"string"
],
"modelId": "string",
"projectId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
labelBins | [LabelwiseLiftChartItem] | true | maxItems: 100 |
Lift charts for the given data source. |
labels | [string] | true | maxItems: 100 |
All available target labels for this insight. |
modelId | string | true | Model Id. | |
projectId | string | true | Project Id. | |
source | string | true | Data source of Lift charts. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout ] |
LabelwiseLiftChartBin
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actual | number | true | Average of actual target values for the rows in the bin. | |
binWeight | number | true | For projects with weights, it is the sum of the weights of all rows in the bins. Otherwise, it is the number of rows in the bin. | |
predicted | number | true | Average of predicted target values for the rows in the bin. |
LabelwiseLiftChartItem
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"label": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [LabelwiseLiftChartBin] | true | maxItems: 60 |
Lift chart data for that label. |
label | string | true | Label name. |
LabelwiseROC
{
"averageModelMetrics": {
"metrics": [
{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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},
{
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},
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},
{
"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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"name": "accuracy",
"numLabelsUsedInCalculation": 0,
"values": [
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],
"source": "validation",
"thresholds": [
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},
"charts": [
{
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"label": "string",
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 1,
"f1Score": 1,
"falseNegativeScore": 0,
"falsePositiveRate": 1,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": -1,
"negativePredictiveValue": 1,
"positivePredictiveValue": 1,
"threshold": 2,
"trueNegativeRate": 1,
"trueNegativeScore": 0,
"truePositiveRate": 1,
"truePositiveScore": 0
}
],
"source": "validation"
}
],
"count": 0,
"labels": [
"string"
],
"next": "http://example.com",
"previous": "http://example.com",
"rocType": "binary",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
averageModelMetrics | AverageModelMetricsField | true | All average model metrics from one data source. | |
charts | [LabelwiseROCItem] | true | ROC data for all labels from one data source. | |
count | integer | false | Number of labels returned on this page. | |
labels | [string] | true | maxItems: 100 |
All available target labels for this insight. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
rocType | string | true | Type of ROC. | |
totalCount | integer | true | Total number of labels across all pages. |
Enumerated Values¶
Property | Value |
---|---|
rocType | [binary , labelwise ] |
LabelwiseROCItem
{
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"label": "string",
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 1,
"f1Score": 1,
"falseNegativeScore": 0,
"falsePositiveRate": 1,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": -1,
"negativePredictiveValue": 1,
"positivePredictiveValue": 1,
"threshold": 2,
"trueNegativeRate": 1,
"trueNegativeScore": 0,
"truePositiveRate": 1,
"truePositiveScore": 0
}
],
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
auc | number | true | Area under the curve. | |
kolmogorovSmirnovMetric | number | true | Kolmogorov-Smirnov metric. | |
label | string | true | Label name. | |
negativeClassPredictions | [number] | true | List of example predictions for the negative class. | |
positiveClassPredictions | [number] | true | List of example predictions for the positive class. | |
rocPoints | [LabelwiseROCPoint] | true | ROC characteristics for label. | |
source | string | true | Data source of ROC characteristics. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout ] |
LabelwiseROCPoint
{
"accuracy": 1,
"f1Score": 1,
"falseNegativeScore": 0,
"falsePositiveRate": 1,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": -1,
"negativePredictiveValue": 1,
"positivePredictiveValue": 1,
"threshold": 2,
"trueNegativeRate": 1,
"trueNegativeScore": 0,
"truePositiveRate": 1,
"truePositiveScore": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
accuracy | number | true | maximum: 1 minimum: 0 |
Accuracy. |
f1Score | number | true | maximum: 1 minimum: 0 |
F1 score. |
falseNegativeScore | integer¦null | true | minimum: 0 |
False negative score. |
falsePositiveRate | number¦null | true | maximum: 1 minimum: 0 |
False positive rate. |
falsePositiveScore | integer¦null | true | minimum: 0 |
False positive score. |
fractionPredictedAsNegative | number¦null | true | Fraction of negative predictions. | |
fractionPredictedAsPositive | number¦null | true | Fraction of positive predictions. | |
liftNegative | number¦null | true | Negative lift. | |
liftPositive | number¦null | true | Positive lift. | |
matthewsCorrelationCoefficient | number | true | maximum: 1 minimum: -1 |
Matthews correlation coefficient. |
negativePredictiveValue | number | true | maximum: 1 minimum: 0 |
Negative predictive value. |
positivePredictiveValue | number | true | maximum: 1 minimum: 0 |
Positive predictive value. |
threshold | number | true | maximum: 2 minimum: 0 |
Threshold. |
trueNegativeRate | number¦null | true | maximum: 1 minimum: 0 |
True negative rate. |
trueNegativeScore | integer¦null | true | minimum: 0 |
True negative score. |
truePositiveRate | number¦null | true | maximum: 1 minimum: 0 |
True positive rate. |
truePositiveScore | integer¦null | true | minimum: 0 |
True positive score. |
LiftBinResponse
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actual | number | true | The average of the actual target values for the rows in the bin. | |
binWeight | number | true | How much data is in the bin. For projects with weights, it is the sum of the weights of all rows in the bins; otherwise, it is the number of rows in the bin. | |
predicted | number | true | The average of predicted values of the target for the rows in the bin. |
LiftChartForDatasetsList
{
"count": 0,
"data": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"datasetId": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Number of results returned on this page. | |
data | [LiftData] | true | Array of lift chart data for dataset, as specified below | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). |
LiftChartResponse
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
]
}
Lift chart data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [LiftBinResponse] | true | The lift chart data for that source, as specified below. |
LiftChartbins
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actual | number | true | The average of the actual target values for the rows in the bin. | |
binWeight | number | true | How much data is in the bin. For projects with weights, it is the sum of the weights of all rows in the bins; otherwise, it is the number of rows in the bin. | |
predicted | number | true | The average of predicted values of the target for the rows in the bin. |
LiftData
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"datasetId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [LiftChartbins] | true | The lift chart data for that source, as specified below. | |
datasetId | string | true | The dataset id of dataset which was used to compute Lift chart. |
ModelConfusionChartClassDetailsForDatasetRetrieve
{
"actualFrequency": [
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
],
"className": "string",
"datasetId": "string",
"modelId": "string",
"predictedFrequency": [
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
],
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actualFrequency | [ActualFrequency] | true | One vs All actual percentage and count in a format specified below sorted by percentage in decreasing order | |
className | string | true | Name of a class for which distribution frequency is requested | |
datasetId | string | true | The dataset to retrieve a Confusion chart from. | |
modelId | string | true | The model to retrieve a Confusion chart from. | |
predictedFrequency | [PredictedFrequency] | true | One vs All predicted percentage and count in a format specified below sorted by percentage in decreasing order | |
projectId | string | true | The project to retrieve a Confusion chart from. |
ModelConfusionChartClassDetailsRetrieveReponseController
{
"actualFrequency": [
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
],
"className": "string",
"predictedFrequency": [
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actualFrequency | [ActualFrequency] | true | One vs all actual percentage and count in a format specified below sorted by percentage in decreasing order | |
className | string | true | Name of a class for which distribution frequency is requested. | |
predictedFrequency | [PredictedFrequency] | true | One vs all predicted percentage and count in a format specified below sorted by percentage in decreasing order |
ModelConfusionChartListResponse
{
"charts": [
{
"columns": [
0
],
"data": {
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
},
"globalMetrics": {
"f1": 0,
"precision": 0,
"recall": 0
},
"numberOfClasses": 0,
"rows": [
0
],
"source": "validation",
"totalMatrixSum": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
charts | [ModelConfusionChartRetrieveResponse] | true | Chart data from all available sources. |
ModelConfusionChartMetadataRetrieveResponse
{
"classNames": [
"string"
],
"globalMetrics": {
"f1": 0,
"precision": 0,
"recall": 0
},
"relevantClassesPositions": [
[
1
]
],
"source": "validation",
"totalMatrixSum": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
classNames | [string] | true | List of all class names in the full confusion matrix, sorted by the orderBy parameter |
|
globalMetrics | GlobalMetrics | true | average metrics across all classes | |
relevantClassesPositions | [array] | true | Matrix to highlight important cell blocks in the confusion chart. Intended to represent a thumbnail view, where the relevantClassesPositions array has a 1 in thumbnail cells that are of interest, and 0 otherwise. The dimensions of the implied thumbnail will not match those of the confusion matrix, e.g. a twenty-class confusion matrix may have a 2x2 thumbnail. | |
source | string | true | Source of the chart. | |
totalMatrixSum | integer | true | minimum: 0 |
Sum of all values in the full confusion matrix (equal to the number of points considered) |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout ] |
ModelConfusionChartRetrieveResponse
{
"columns": [
0
],
"data": {
"classMetrics": [
{
"actualCount": 0,
"className": "string",
"confusionMatrixOneVsAll": [
[
0
]
],
"f1": 0,
"precision": 0,
"predictedCount": 0,
"recall": 0,
"wasActualPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
],
"wasPredictedPercentages": [
{
"otherClassName": "string",
"percentage": 0
}
]
}
],
"classes": [
"string"
],
"colClasses": [
"string"
],
"confusionMatrix": [
[
0
]
],
"rowClasses": [
"string"
]
},
"globalMetrics": {
"f1": 0,
"precision": 0,
"recall": 0
},
"numberOfClasses": 0,
"rows": [
0
],
"source": "validation",
"totalMatrixSum": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
columns | [integer] | true | [colStart, colEnd] column dimension of confusion matrix in response | |
data | ConfusionChartData | true | confusion chart data with the format below. | |
globalMetrics | GlobalMetrics | true | average metrics across all classes | |
numberOfClasses | integer | true | count of classes in full confusion matrix. | |
rows | [integer] | true | [rowStart, rowEnd] row dimension of confusion matrix in response | |
source | string | true | source of the chart | |
totalMatrixSum | integer | true | sum of all values in full confusion matrix |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout ] |
ModelLiftChartListResponse
{
"charts": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"source": "validation"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
charts | [ModelLiftChartResponse] | true | List of lift chart data from all available sources. |
ModelLiftChartResponse
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [LiftBinResponse] | true | The lift chart data for that source, as specified below. | |
source | string | true | Source of the data. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
ModelResidualsChartData
{
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
}
Chart data from the validation data source
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
coefficientOfDetermination | number | true | Also known as the r-squared value. This value is calculated over the downsampled dataset, not the full input | |
data | [array] | true | The rows of chart data in [actual, predicted, residual, row number] form. If the row number was not available at the time of model creation, the row number will be null. NOTE: In DataRobot v5.2, the row number will not be included. | |
histogram | [ModelResidualsHistogram] | true | Data to plot a histogram of residual values | |
residualMean | number | true | The arithmetic mean of the predicted value minus the actual value over the downsampled dataset | |
standardDeviation | number | true | A measure of deviation from the group as a whole |
ModelResidualsHistogram
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
intervalEnd | number | true | The interval end. For all but the last interval, the end value is exclusive | |
intervalStart | number | true | The interval start | |
occurrences | integer | true | The number of times the predicted value fits within the interval |
ModelResidualsList
{
"residuals": {
"crossValidation": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"holdout": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"validation": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
}
}
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
residuals | ModelResidualsSource | true | Residuals chart data from all available sources |
ModelResidualsSource
{
"crossValidation": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"holdout": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"validation": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
}
}
Residuals chart data from all available sources
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
crossValidation | ModelResidualsChartData | false | Chart data from the validation data source | |
holdout | ModelResidualsChartData | false | Chart data from the validation data source | |
validation | ModelResidualsChartData | false | Chart data from the validation data source |
ModelRocCurveListResponse
{
"charts": [
{
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
],
"source": "validation"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
charts | [ModelRocCurveResponse] | true | List of ROC curve data from all available sources. |
ModelRocCurveResponse
{
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
],
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
auc | number¦null | true | AUC value | |
kolmogorovSmirnovMetric | number¦null | true | Kolmogorov-Smirnov metric value | |
negativeClassPredictions | [number] | true | List of example predictions for the negative class. | |
positiveClassPredictions | [number] | true | List of example predictions for the positive class. | |
rocPoints | [RocPointsResponse] | true | The ROC curve data for that source, as specified below. | |
source | string | true | Source of the data. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
ModelXrayMetadataDatetimeDataResponse
{
"backtestIndex": "string",
"sources": [
"training"
],
"status": "INPROGRESS"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestIndex | string | true | The backtest index. For example: 0 , 1 , ..., 20 , holdout , startstop . |
|
sources | [string] | true | List of sources available for the model. | |
status | string | true | Status of the job. |
Enumerated Values¶
Property | Value |
---|---|
status | [INPROGRESS , COMPLETED , NOT_COMPLETED ] |
ModelXrayMetadataDatetimeResponse
{
"data": [
{
"backtestIndex": "string",
"sources": [
"training"
],
"status": "INPROGRESS"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | [ModelXrayMetadataDatetimeDataResponse] | true | List of objects with status and sources of each backtest. |
ModelXrayMetadataResponse
{
"sources": [
"training"
],
"status": "INPROGRESS"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
sources | [string] | true | List of sources available for the model. | |
status | string | true | Status of the job. |
Enumerated Values¶
Property | Value |
---|---|
status | [INPROGRESS , COMPLETED , NOT_COMPLETED ] |
MulticategoricalHistogram
{
"featureName": "string",
"histogram": [
{
"label": "string",
"plot": [
{
"labelRelevance": 1,
"rowCount": 0,
"rowPct": 100
},
{
"labelRelevance": 1,
"rowCount": 0,
"rowPct": 100
}
]
}
],
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureName | string | true | Feature name. | |
histogram | [MulticategoricalHistogramItem] | true | maxItems: 1000 minItems: 1 |
Feature histogram. |
projectId | string | true | Project Id. |
MulticategoricalHistogramItem
{
"label": "string",
"plot": [
{
"labelRelevance": 1,
"rowCount": 0,
"rowPct": 100
},
{
"labelRelevance": 1,
"rowCount": 0,
"rowPct": 100
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
label | string | true | Label name. | |
plot | [LabelRelevancePlot] | true | maxItems: 2 minItems: 2 |
Relevance histogram for label. |
MulticategoricalInvalidFormatErrorData
{
"errors": [
{
"error": "string",
"feature": "string",
"rowData": "string",
"rowIndex": 0
}
]
}
Error data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
errors | [MulticategoricalInvalidFormatErrorList] | true | maxItems: 100 |
Multicategorical format errors. |
MulticategoricalInvalidFormatErrorList
{
"error": "string",
"feature": "string",
"rowData": "string",
"rowIndex": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
error | string | true | Error type. | |
feature | string | true | Feature name. | |
rowData | string¦null | true | Content of the row containing format error. | |
rowIndex | integer¦null | true | Row index of the row containing format error. |
MulticategoricalInvalidFormatResponse
{
"data": {
"errors": [
{
"error": "string",
"feature": "string",
"rowData": "string",
"rowIndex": 0
}
]
},
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | MulticategoricalInvalidFormatErrorData | true | Error data. | |
projectId | string | true | The ID of the project this request is associated with. |
MulticlassDatetimeFeatureEffectsResponse
{
"backtestIndex": "string",
"count": 0,
"data": [
{
"class": "string",
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
],
"modelId": "string",
"next": "http://example.com",
"previous": "http://example.com",
"projectId": "string",
"source": "string",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestIndex | string | true | The backtest index. For example: 0 , 1 , ..., 20 , holdout , startstop . |
|
count | integer | false | Number of items returned on this page. | |
data | [MulticlassFeatureEffects] | true | A list of feature effects scores for each class in multiclass project. | |
modelId | string | true | The model ID | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
projectId | string | true | The project ID | |
source | string | true | Models data source. | |
totalCount | integer | true | The total number of items across all pages. |
MulticlassFeatureEffectCreate
{
"features": [
"string"
],
"rowCount": 10,
"topNFeatures": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
features | [string]¦null | false | maxItems: 20000 |
The list of features to use to calculate feature effects. |
rowCount | integer¦null | false | maximum: 100000 minimum: 10 |
The number of rows from dataset to use for Feature Impact calculation. |
topNFeatures | integer¦null | false | maximum: 1000 minimum: 0 (exclusive) |
Number of top features (ranked by feature impact) to use to calculate feature effects. |
MulticlassFeatureEffectDatetimeCreate
{
"backtestIndex": "string",
"features": [
"string"
],
"rowCount": 10,
"topNFeatures": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestIndex | string | true | The backtest index. For example: 0 , 1 , ..., 20 , holdout , startstop . |
|
features | [string]¦null | false | maxItems: 20000 |
The list of features to use to calculate feature effects. |
rowCount | integer¦null | false | maximum: 100000 minimum: 10 |
The number of rows from dataset to use for Feature Impact calculation. |
topNFeatures | integer¦null | false | maximum: 1000 minimum: 0 (exclusive) |
Number of top features (ranked by feature impact) to use to calculate feature effects. |
MulticlassFeatureEffects
{
"class": "string",
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
class | string | true | Target class label. | |
featureImpactScore | number | true | Feature impact score. | |
featureName | string | true | Name of the feature. | |
featureType | string | true | Feature type, either numeric or categorical. | |
isBinnable | boolean | true | Whether values can be grouped into bins. | |
isScalable | boolean¦null | true | Whether numeric feature values can be reported on a log scale. | |
partialDependence | PartialDependence | false | Partial dependence results. Can be missing if no data for the feature was qualified to generate the insight. | |
predictedVsActual | PredictedVsActual | false | Predicted versus actual results. Can be missing if no data for the feature was qualified to generate the insight. | |
weightLabel | string¦null | true | Weight label if weight was configured for the project. |
MulticlassFeatureEffectsResponse
{
"count": 0,
"data": [
{
"class": "string",
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
],
"modelId": "string",
"next": "http://example.com",
"previous": "http://example.com",
"projectId": "string",
"source": "string",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [MulticlassFeatureEffects] | true | A list of feature effects scores for each class in multiclass project. | |
modelId | string | true | The model ID | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
projectId | string | true | The project ID | |
source | string | true | Models data source. | |
totalCount | integer | true | The total number of items across all pages. |
MulticlassFeatureImpact
{
"class": "string",
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
class | string | true | Target class label. | |
featureImpacts | [FeatureImpactItem] | true | maxItems: 1000 |
A list which contains feature impact scores for each feature used by a model. If the model has more than 1000 features, the most important 1000 features are returned. |
MulticlassFeatureImpactResponse
{
"classFeatureImpacts": [
{
"class": "string",
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
]
}
],
"count": 0,
"next": "http://example.com",
"previous": "http://example.com",
"ranRedundancyDetection": true,
"shapBased": true
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
classFeatureImpacts | [MulticlassFeatureImpact] | true | A list of feature importance scores for each class in multiclass project. | |
count | integer | true | Number of feature impact records in a given batch. | |
next | string(uri)¦null | true | URL for the next page of results or null . |
|
previous | string(uri)¦null | true | URL for the next page of results or null . |
|
ranRedundancyDetection | boolean | true | Indicates whether redundant feature identification was run while calculating this feature impact. Currently always False, as redundant feature identification isn't supported for multiclass in DataRobot. | |
shapBased | boolean | true | Indicates whether feature impact was calculated using Shapley values. Currently always False , as SHAP isn't supported for multiclass in DataRobot. |
MulticlassLiftBinResponse
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [LiftBinResponse] | true | The lift chart data for that source, as specified below. | |
targetClass | string | true | Target class for the lift chart. |
MulticlassLiftChartForDatasetsList
{
"count": 0,
"data": [
{
"classBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
],
"datasetId": "string"
}
],
"modelId": "string",
"next": "http://example.com",
"previous": "http://example.com",
"projectId": "string",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Number of results returned on this page. | |
data | [MulticlassLiftData] | true | Array of multiclass lift chart data for dataset, as specified below. | |
modelId | string | true | The model id to which the chart data belongs. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
projectId | string | true | The project id to which the chart data belongs. | |
totalCount | integer | true | Total count of multiclass lift charts matching to the query condition. |
MulticlassLiftData
{
"classBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
],
"datasetId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
classBins | [MulticlassLiftDataClassBins] | true | List of lift chart data for each target class. | |
datasetId | string | true | The dataset id of dataset which was used to compute Lift chart. |
MulticlassLiftDataClassBins
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [LiftChartbins] | true | The lift chart data for that source and class, as specified below. | |
targetClass | string | true | The target class for the lift chart. |
MulticlassModelLiftChartResponse
{
"classBins": [
{
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
],
"targetClass": "string"
}
],
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
classBins | [MulticlassLiftBinResponse] | true | List of lift chart data for each target class. | |
source | string | true | Source of the data |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout ] |
MultiseriesHistogramsBin
{
"count": 0,
"left": 0,
"right": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | The value count of the bin | |
left | any | true | The inclusive left boundary of the bin. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | number | false | none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
right | any | true | The exclusive right boundary of the bin. The last bin has an inclusive right boundary. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | number | false | none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
MultiseriesHistogramsRetrieveResponse
{
"bins": [
{
"count": 0,
"left": 0,
"right": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
bins | [MultiseriesHistogramsBin] | true | List of bins representing histogram. |
Numeric
{
"allData": 0,
"insightName": "min",
"perCluster": [
{
"clusterName": "string",
"statistic": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
allData | number¦null | true | Statistic value for all data. | |
insightName | string | true | Insight name. | |
perCluster | [PerClusterNumeric] | true | Statistic values for for each cluster. |
Enumerated Values¶
Property | Value |
---|---|
insightName | [min , max , median , avg , firstQuartile , thirdQuartile , missingRowsPercent ] |
NumericFeature
{
"featureImpact": 0,
"featureName": "string",
"featureType": "numeric",
"insights": [
{
"allData": 0,
"insightName": "min",
"perCluster": [
{
"clusterName": "string",
"statistic": 0
}
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureImpact | number¦null | false | Feature Impact score. | |
featureName | string | true | Feature name. | |
featureType | string | true | Feature Type. | |
insights | [Numeric] | true | A list of Cluster Insights for a feature. |
Enumerated Values¶
Property | Value |
---|---|
featureType | numeric |
PairwiseManualSelectionCreatePayload
{
"columnLabels": [
"string"
],
"featureName": "string",
"multilabelInsightsKey": "string",
"name": "string",
"projectId": "string",
"rowLabels": [
"string"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
columnLabels | [string] | true | maxItems: 10 minItems: 1 |
Manually selected column labels. |
featureName | string¦null | true | Name of the feature the request is related to | |
multilabelInsightsKey | string | true | Key for multilabel insights, unique per project, feature, and EDA stage. The most recent key can be retrieved via [GET /api/v2/projects/{projectId}/features/][get-apiv2projectsprojectidfeatures] or [GET /api/v2/projects/{projectId}/features/{featurename:featureName}/][get-apiv2projectsprojectidfeaturesfeaturenamefeaturename] | |
name | string | true | maxLength: 100 |
Name for the set of manually selected labels. |
projectId | string¦null | true | ID of the project the request is related to. | |
rowLabels | [string] | true | maxItems: 10 minItems: 1 |
Manually selected row labels. |
PairwiseManualSelectionCreateResponse
{
"id": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
id | string | true | ID of the label set. |
PairwiseManualSelectionCreatedItem
{
"columnLabels": [
"string"
],
"id": "string",
"name": "string",
"rowLabels": [
"string"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
columnLabels | [string] | true | maxItems: 10 minItems: 1 |
Manually selected column labels. |
id | string | true | Id of the manually selected labels set | |
name | string | true | maxLength: 100 |
Name for the set of manually selected labels. |
rowLabels | [string] | true | maxItems: 10 minItems: 1 |
Manually selected row labels. |
PairwiseManualSelectionResponse
{
"manualSelectionId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
manualSelectionId | string | true | ID of the deleted or updated label set. |
PairwiseManualSelectionUpdateRequest
{
"name": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
name | string | true | maxLength: 100 |
Name for the set of manually selected labels. |
PairwiseManualSelectionsRetrieveResponse
{
"data": [
{
"columnLabels": [
"string"
],
"id": "string",
"name": "string",
"rowLabels": [
"string"
]
}
],
"featureName": "string",
"multilabelInsightsKey": "string",
"projectId": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | [PairwiseManualSelectionCreatedItem] | true | List of manually selected labels sets | |
featureName | string¦null | true | Name of the feature the request is related to | |
multilabelInsightsKey | string | true | Key for multilabel insights, unique per project, feature, and EDA stage. The most recent key can be retrieved via [GET /api/v2/projects/{projectId}/features/][get-apiv2projectsprojectidfeatures] or [GET /api/v2/projects/{projectId}/features/{featurename:featureName}/][get-apiv2projectsprojectidfeaturesfeaturenamefeaturename] | |
projectId | string¦null | true | ID of the project the request is related to. |
PairwiseStatisticsItem
{
"labelConfiguration": [
{
"label": "string",
"relevance": 1
},
{
"label": "string",
"relevance": 1
}
],
"statisticValue": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
labelConfiguration | [PairwiseStatisticsLabelConfiguration] | true | maxItems: 2 minItems: 2 |
Configuration of all labels. |
statisticValue | number¦null | true | Statistic value for the given label configuration. |
PairwiseStatisticsLabelConfiguration
{
"label": "string",
"relevance": 1
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
label | string | true | Label name. | |
relevance | integer | false | maximum: 1 minimum: 0 |
Relevance value of the label. |
PairwiseStatisticsResponse
{
"data": [
{
"labelConfiguration": [
{
"label": "string",
"relevance": 1
},
{
"label": "string",
"relevance": 1
}
],
"statisticValue": 0
}
],
"featureName": "string",
"projectId": "stringstringstringstring",
"statisticType": "conditionalProbability"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | [PairwiseStatisticsItem] | true | Statistic values. | |
featureName | string | true | Feature name. | |
projectId | string | true | maxLength: 24 minLength: 24 minLength: 24 |
Project Id. |
statisticType | string | true | Pairwise statistic type. |
Enumerated Values¶
Property | Value |
---|---|
statisticType | [conditionalProbability , correlation , jointProbability ] |
PartialDependence
{
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
}
Partial dependence results. Can be missing if no data for the feature was qualified to generate the insight.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | [PartialDependenceData] | true | Partial dependence results. | |
isCapped | boolean | true | Indicates whether the data for computation is capped. |
PartialDependenceData
{
"dependence": 0,
"label": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
dependence | number | true | The value of partial dependence. | |
label | string | true | Contains the label for categorical and numeric features as string. |
PayoffMatricesCreate
{
"falseNegativeValue": 0,
"falsePositiveValue": 0,
"name": "string",
"trueNegativeValue": 0,
"truePositiveValue": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
falseNegativeValue | number | true | False negative value to use for profit curve calculation. | |
falsePositiveValue | number | true | False positive value to use for profit curve calculation. | |
name | string | true | Name of the payoff matrix to be created. | |
trueNegativeValue | number | true | True negative value to use for profit curve calculation. | |
truePositiveValue | number | true | True positive value to use for profit curve calculation. |
PayoffMatricesListResponse
{
"count": 0,
"data": [
{
"falseNegativeValue": 0,
"falsePositiveValue": 0,
"id": "string",
"name": "string",
"projectId": "string",
"trueNegativeValue": 0,
"truePositiveValue": 0
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Number of items in current page. | |
data | [PayoffMatricesResponse] | true | Payoff matrices for a project. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page) | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page) | |
totalCount | integer | true | Total number of items. |
PayoffMatricesResponse
{
"falseNegativeValue": 0,
"falsePositiveValue": 0,
"id": "string",
"name": "string",
"projectId": "string",
"trueNegativeValue": 0,
"truePositiveValue": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
falseNegativeValue | number | true | Payoff value for false negatives used in profit curve calculation. | |
falsePositiveValue | number | true | Payoff value for false positives used in profit curve calculation. | |
id | string | true | ObjectId of the payoff matrix. | |
name | string | true | Label for the payoff matrix. | |
projectId | string | true | ID of the project associated with the payoff matrix. | |
trueNegativeValue | number | true | Payoff value for true negatives used in profit curve calculation. | |
truePositiveValue | number | true | Payoff value for true positives used in profit curve calculation. |
PerClassAccuracy
{
"className": "string",
"metrics": [
{
"metric": "AUC",
"value": 1
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
className | string | true | The name of the class value for the categorical feature. | |
metrics | [AccuracyMetrics] | true | An array of metric scores. |
PerClassFairness
{
"absoluteValue": 0,
"className": "string",
"entriesCount": 0,
"isStatisticallySignificant": true,
"value": 1
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
absoluteValue | number | true | minimum: 0 |
Absolute fairness score for the class |
className | string | true | Name of the protected class the score is calculated for. | |
entriesCount | integer | true | minimum: 0 |
The number of entries of the class in the analysed data. |
isStatisticallySignificant | boolean | true | Flag to tell whether the score can be treated as statistically significant. In other words, whether we are confident enough with the score for this protected class. | |
value | number | true | maximum: 1 minimum: 0 |
The relative fairness score for the class. |
PerClusterCategorical
{
"allOther": 100,
"clusterName": "string",
"missingRowsPercent": 100,
"perValueStatistics": [
{
"categoryLevel": "string",
"frequency": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
allOther | number¦null | false | maximum: 100 minimum: 0 |
A percentage of rows that do not have any of these values or categories. |
clusterName | string | true | Cluster name. | |
missingRowsPercent | number¦null | false | maximum: 100 minimum: 0 |
A percentage of all rows that have a missing value for this feature. |
perValueStatistics | [PerValueStatisticsListItem] | true | Statistic value for feature values in all data or a cluster. |
PerClusterGeospatial
{
"clusterName": "string",
"representativeLocations": [
[
-180
]
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
clusterName | string | true | maxLength: 50 minLength: 1 minLength: 1 |
Cluster name. |
representativeLocations | [array] | true | maxItems: 1000 |
A list of latitude and longitude location list |
PerClusterImage
{
"clusterName": "string",
"images": [
"string"
],
"percentageOfMissingImages": 100
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
clusterName | string | true | Cluster name. | |
images | [string] | true | A list of b64 encoded images. | |
percentageOfMissingImages | number | true | maximum: 100 minimum: 0 |
A percentage of image rows that have a missing value for this feature. |
PerClusterNumeric
{
"clusterName": "string",
"statistic": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
clusterName | string | true | Cluster name. | |
statistic | number¦null | true | Statistic value for this cluster. |
PerClusterText
{
"clusterName": "string",
"missingRowsPercent": 100,
"perValueStatistics": [
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
clusterName | string | true | Cluster name. | |
missingRowsPercent | number¦null | false | maximum: 100 minimum: 0 |
A percentage of all rows that have a missing value for this feature. |
perValueStatistics | [PerValueStatisticTextListItem] | true | Statistic value for feature values in all data or a cluster. |
PerValueStatisticTextListItem
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
contextualExtracts | [string] | true | Contextual extracts that show context for the n-gram. | |
importance | number | true | Importance value for this n-gram. | |
ngram | string | true | An n-gram. |
PerValueStatistics
{
"allOther": 100,
"missingRowsPercent": 100,
"perValueStatistics": [
{
"categoryLevel": "string",
"frequency": 0
}
]
}
Statistics for all data for different feature values.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
allOther | number¦null | false | maximum: 100 minimum: 0 |
A percentage of rows that do not have any of these values or categories. |
missingRowsPercent | number¦null | false | maximum: 100 minimum: 0 |
A percentage of all rows that have a missing value for this feature. |
perValueStatistics | [PerValueStatisticsListItem] | true | Statistic value for feature values in all data or a cluster. |
PerValueStatisticsListItem
{
"categoryLevel": "string",
"frequency": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
categoryLevel | string | true | A category level. | |
frequency | number | true | Statistic value for this cluster. |
PermutationFeatureImpactCreatePayload
{
"backtest": 19,
"rowCount": 10
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtest | any | false | The backtest value used for Feature Impact computation. Applicable for datetime aware models. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | maximum: 19 minimum: 0 |
none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
rowCount | integer | false | maximum: 100000 minimum: 10 |
The sample size to use for Feature Impact computation. It is possible to re-compute Feature Impact with a different row count. |
Enumerated Values¶
Property | Value |
---|---|
anonymous | holdout |
PermutationFeatureImpactResponse
{
"backtest": 19,
"count": 0,
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"ranRedundancyDetection": true,
"rowCount": 0,
"shapBased": true
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtest | any | true | The backtest model used to compute Feature Impact.Defined for datetime aware models. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | maximum: 19 minimum: 0 |
none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | Number of feature impact records in a given batch. | |
featureImpacts | [FeatureImpactItem] | true | maxItems: 1000 |
A list which contains feature impact scores for each feature used by a model. If the model has more than 1000 features, the most important 1000 features are returned. |
next | string(uri)¦null | true | URL for the next page of results or null . |
|
previous | string(uri)¦null | true | URL for the next page of results or null . |
|
ranRedundancyDetection | boolean | true | Indicates whether redundant feature identification was run while calculating this feature impact. | |
rowCount | integer¦null | true | The number of rows that was used to calculate feature impact. For the feature impact calculated with the default logic, without specifying the rowCount , we return null here. |
|
shapBased | boolean | true | Indicates whether feature impact was calculated using Shapley values. True for anomaly detection models when the project is unsupervised, as permutation approach is not applicable. Note that supervised projects must use an alternative route for SHAP impact: /api/v2/projects/(projectId)/models/(modelId)/shapImpact/ |
Enumerated Values¶
Property | Value |
---|---|
anonymous | holdout |
PredictedFrequency
{
"otherClassName": "string",
"percentage": 100,
"value": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
otherClassName | string | true | The name of the class. | |
percentage | number | true | maximum: 100 minimum: 0 |
the percentage of the times this class was actual when classMetrics.className is predicted (from 0 to 100) |
value | integer | true | minimum: 0 |
The count of the times this class was actual classMetrics.className when it was predicted |
PredictedPercentages
{
"otherClassName": "string",
"percentage": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
otherClassName | string | true | the name of the class | |
percentage | number | true | the percentage of the times this class was actual when classMetrics.className is predicted |
PredictedVsActual
{
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
}
Predicted versus actual results. Can be missing if no data for the feature was qualified to generate the insight.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | [PredictedVsActualData] | true | Predicted versus actual results. | |
isCapped | boolean | true | Indicates whether the data for computation is capped. | |
logScaledData | [PredictedVsActualData] | true | Predicted versus actual results in a log scale. |
PredictedVsActualData
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
actual | number¦null | true | Actual value. null for 0 rows bins and unsupervised time series models. |
|
bin | [string] | false | For numeric features contains labels for left and right bin limits | |
label | string | true | Contains label for categorical features; For numeric features contains range or numeric value. | |
predicted | number¦null | true | Predicted value. null for 0 rows bins. |
|
rowCount | integer | true | Number of rows for the label and bin. |
ResidualsChartForDatasets
{
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"datasetId": "string",
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
coefficientOfDetermination | number | true | Also known as the r-squared value. This value is calculated over the downsampled dataset, not the full input. | |
data | [array] | true | The rows of chart data in [actual, predicted, residual, row number] form. If the row number was not available at the time of model creation, the row number will be null . |
|
datasetId | string | true | The dataset ID. | |
histogram | [Histogram] | true | Data to plot a histogram of residual values. The object contains three keys, intervalStart, intervalEnd, and occurrences, the number of times the predicted value fits within that interval. For all but the last interval, the end value is exclusive. | |
residualMean | number | true | The arithmetic mean of the predicted value minus the actual value over the downsampled dataset. | |
standardDeviation | number | true | The Standard Deviation value measures variation in the dataset. A low value indicates that the data points tend to be close to the mean; a high value indicates that the data points are spread over a wider range of values. |
ResidualsChartForDatasetsList
{
"count": 0,
"data": [
{
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"datasetId": "string",
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
}
],
"modelId": "string",
"next": "http://example.com",
"previous": "http://example.com",
"projectId": "string",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [ResidualsChartForDatasets] | true | List of residuals charts for dataset. | |
modelId | string | true | The model ID. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
projectId | string | true | The project ID. | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveFeatureEffectsIndividualResponse
{
"backtestIndex": "string",
"data": {
"featureEffects": [
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
]
},
"dataSliceId": "string",
"entityId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestIndex | string¦null | false | The backtest index. For example: 0 , 1 , ..., 20 , holdout . |
|
data | FeatureEffectsInsightResponse | true | Feature effects data. | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
source | string | false | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , training , backtest_0 , backtest_1 , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 , holdout , backtest_0_training , backtest_1_training , backtest_2_training , backtest_3_training , backtest_4_training , backtest_5_training , backtest_6_training , backtest_7_training , backtest_8_training , backtest_9_training , backtest_10_training , backtest_11_training , backtest_12_training , backtest_13_training , backtest_14_training , backtest_15_training , backtest_16_training , backtest_17_training , backtest_18_training , backtest_19_training , backtest_20_training , holdout_training ] |
RetrieveFeatureEffectsPaginatedResponse
{
"count": 0,
"data": [
{
"backtestIndex": "string",
"data": {
"featureEffects": [
{
"featureImpactScore": 0,
"featureName": "string",
"featureType": "string",
"isBinnable": true,
"isScalable": true,
"partialDependence": {
"data": [
{
"dependence": 0,
"label": "string"
}
],
"isCapped": true
},
"predictedVsActual": {
"data": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
],
"isCapped": true,
"logScaledData": [
{
"actual": 0,
"bin": [
"string"
],
"label": "string",
"predicted": 0,
"rowCount": 0
}
]
},
"weightLabel": "string"
}
]
},
"dataSliceId": "string",
"entityId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveFeatureEffectsIndividualResponse] | true | maxItems: 10 |
List of paginated feature effects insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveFeatureImpactIndividualResponse
{
"data": {
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
],
"ranRedundancyDetection": true,
"rowCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"id": "string",
"projectId": "string",
"source": "training"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | FeatureImpactInsightResponse | true | Feature impact data. | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
source | string | false | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [training , backtest_2Training , backtest_3Training , backtest_4Training , backtest_5Training , backtest_6Training , backtest_7Training , backtest_8Training , backtest_9Training , backtest_10Training , backtest_11Training , backtest_12Training , backtest_13Training , backtest_14Training , backtest_15Training , backtest_16Training , backtest_17Training , backtest_18Training , backtest_19Training , backtest_20Training , backtest_1Training , holdoutTraining ] |
RetrieveFeatureImpactPaginatedResponse
{
"count": 0,
"data": [
{
"data": {
"featureImpacts": [
{
"featureName": "string",
"impactNormalized": 1,
"impactUnnormalized": 0,
"parentFeatureName": "string",
"redundantWith": "string"
}
],
"ranRedundancyDetection": true,
"rowCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"id": "string",
"projectId": "string",
"source": "training"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveFeatureImpactIndividualResponse] | true | maxItems: 2 |
List of paginated feature impact insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveLiftChartIndividualResponse
{
"data": {
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | LiftChartResponse | true | Lift chart data. | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
externalDatasetId | string¦null | false | The ID of the external dataset. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
source | string | false | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout , externalTestSet , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
RetrieveLiftChartPaginatedResponse
{
"count": 0,
"data": [
{
"data": {
"bins": [
{
"actual": 0,
"binWeight": 0,
"predicted": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveLiftChartIndividualResponse] | true | maxItems: 10 |
List of paginated lift chart insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveResidualsIndividualResponse
{
"data": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | ModelResidualsChartData | true | Chart data from the validation data source | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
externalDatasetId | string¦null | false | The ID of the external dataset. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
source | string | false | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout , externalTestSet ] |
RetrieveResidualsPaginatedResponse
{
"count": 0,
"data": [
{
"data": {
"coefficientOfDetermination": 0,
"data": [
[
0
]
],
"histogram": [
{
"intervalEnd": 0,
"intervalStart": 0,
"occurrences": 0
}
],
"residualMean": 0,
"standardDeviation": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveResidualsIndividualResponse] | true | maxItems: 10 |
List of paginated residuals insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveRocCurveIndividualResponse
{
"data": {
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | RocCurveResponse | true | Roc curve data. | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
externalDatasetId | string¦null | false | The ID of the external dataset. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
source | string | false | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [validation , crossValidation , holdout , externalTestSet , backtest_2 , backtest_3 , backtest_4 , backtest_5 , backtest_6 , backtest_7 , backtest_8 , backtest_9 , backtest_10 , backtest_11 , backtest_12 , backtest_13 , backtest_14 , backtest_15 , backtest_16 , backtest_17 , backtest_18 , backtest_19 , backtest_20 ] |
RetrieveRocCurvePaginatedResponse
{
"count": 0,
"data": [
{
"data": {
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"source": "validation"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveRocCurveIndividualResponse] | true | maxItems: 10 |
List of paginated roc curve insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveShapDistributionsIndividualResponse
{
"data": {
"features": [
{
"feature": "string",
"featureType": "T",
"impactNormalized": 1,
"impactUnnormalized": 0,
"shapValues": [
{
"featureRank": 0,
"featureValue": 0,
"predictionValue": 0,
"rowIndex": 0,
"shapValue": 0
}
]
}
],
"totalFeaturesCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | ShapDistributionsData | true | SHAP distributions data. | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
externalDatasetId | string¦null | false | The ID of the external dataset. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
quickCompute | boolean | false | Whether the insight was computed using the quickCompute setting. | |
source | string | false | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , externalTestSet , holdout , holdout_training , training , validation ] |
RetrieveShapDistributionsPaginatedResponse
{
"count": 0,
"data": [
{
"data": {
"features": [
{
"feature": "string",
"featureType": "T",
"impactNormalized": 1,
"impactUnnormalized": 0,
"shapValues": [
{
"featureRank": 0,
"featureValue": 0,
"predictionValue": 0,
"rowIndex": 0,
"shapValue": 0
}
]
}
],
"totalFeaturesCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveShapDistributionsIndividualResponse] | true | maxItems: 10 |
List of paginated SHAP distributions insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveShapImpactIndividualResponse
{
"data": {
"baseValue": [
0
],
"link": "string",
"quickCompute": true,
"rowCount": 0,
"shapImpacts": [
{
"featureName": "string",
"impactNormalized": 0,
"impactUnnormalized": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | ShapImpactData | true | SHAP impact data. | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
externalDatasetId | string¦null | false | The ID of the external dataset. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
quickCompute | boolean | false | Whether the insight was computed using the quickCompute setting. | |
source | string | false | Subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , externalTestSet , holdout , holdout_training , training , validation ] |
RetrieveShapImpactPaginatedResponse
{
"count": 0,
"data": [
{
"data": {
"baseValue": [
0
],
"link": "string",
"quickCompute": true,
"rowCount": 0,
"shapImpacts": [
{
"featureName": "string",
"impactNormalized": 0,
"impactUnnormalized": 0
}
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveShapImpactIndividualResponse] | true | maxItems: 10 |
List of paginated SHAP impact insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveShapMatrixIndividualResponse
{
"data": {
"baseValue": [
0
],
"colnames": [
"string"
],
"linkFunction": "string",
"matrix": [
[
0
]
],
"rowIndex": [
0
],
"timeSeriesRowIndex": [
[
0
]
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | ShapMatrixData | true | SHAP matrix data. | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
externalDatasetId | string¦null | false | The ID of the external dataset. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
quickCompute | boolean | false | Whether the insight was computed using the quickCompute setting. | |
source | string | false | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , externalTestSet , holdout , holdout_training , training , validation ] |
RetrieveShapMatrixPaginatedResponse
{
"count": 0,
"data": [
{
"data": {
"baseValue": [
0
],
"colnames": [
"string"
],
"linkFunction": "string",
"matrix": [
[
0
]
],
"rowIndex": [
0
],
"timeSeriesRowIndex": [
[
0
]
]
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveShapMatrixIndividualResponse] | true | maxItems: 10 |
List of paginated SHAP matrix insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RetrieveShapPreviewIndividualResponse
{
"data": {
"previews": [
{
"predictionValue": 0,
"previewValues": [
{
"featureName": "string",
"featureRank": 0,
"featureValue": "string",
"hasTextExplanations": true,
"isImage": true,
"shapValue": 0,
"textExplanations": [
"string"
]
}
],
"rowIndex": 0,
"totalPreviewFeatures": 0
}
],
"previewsCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | ShapPreviewData | true | SHAP preview data. | |
dataSliceId | string¦null | false | ID of the data slice. | |
entityId | string | false | ID of the model. | |
externalDatasetId | string¦null | false | The ID of the external dataset. | |
id | string | true | ID of the created insight. | |
projectId | string | false | ID of the project. | |
quickCompute | boolean | false | Whether the insight was computed using the quickCompute setting. | |
source | string | false | The subset of data used to compute the insight. |
Enumerated Values¶
Property | Value |
---|---|
source | [backtest_0 , backtest_0_training , backtest_1 , backtest_10 , backtest_10_training , backtest_11 , backtest_11_training , backtest_12 , backtest_12_training , backtest_13 , backtest_13_training , backtest_14 , backtest_14_training , backtest_15 , backtest_15_training , backtest_16 , backtest_16_training , backtest_17 , backtest_17_training , backtest_18 , backtest_18_training , backtest_19 , backtest_19_training , backtest_1_training , backtest_2 , backtest_20 , backtest_20_training , backtest_2_training , backtest_3 , backtest_3_training , backtest_4 , backtest_4_training , backtest_5 , backtest_5_training , backtest_6 , backtest_6_training , backtest_7 , backtest_7_training , backtest_8 , backtest_8_training , backtest_9 , backtest_9_training , externalTestSet , holdout , holdout_training , training , validation ] |
RetrieveShapPreviewPaginatedResponse
{
"count": 0,
"data": [
{
"data": {
"previews": [
{
"predictionValue": 0,
"previewValues": [
{
"featureName": "string",
"featureRank": 0,
"featureValue": "string",
"hasTextExplanations": true,
"isImage": true,
"shapValue": 0,
"textExplanations": [
"string"
]
}
],
"rowIndex": 0,
"totalPreviewFeatures": 0
}
],
"previewsCount": 0
},
"dataSliceId": "string",
"entityId": "string",
"externalDatasetId": "string",
"id": "string",
"projectId": "string",
"quickCompute": true,
"source": "backtest_0"
}
],
"next": "http://example.com",
"previous": "http://example.com",
"totalCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RetrieveShapPreviewIndividualResponse] | true | maxItems: 10 |
List of paginated SHAP preview insights. |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). | |
totalCount | integer | true | The total number of items across all pages. |
RocCurveForDatasets
{
"datasetId": "string",
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": {
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
datasetId | string | true | The ID of dataset which was used to compute ROC curve. | |
negativeClassPredictions | [number] | true | List of example predictions for the negative class. | |
positiveClassPredictions | [number] | true | List of example predictions for the negative class. | |
rocPoints | RocPointsResponse | true | none |
RocCurveForDatasetsList
{
"count": 0,
"data": [
{
"datasetId": "string",
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": {
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
}
],
"next": "http://example.com",
"previous": "http://example.com"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [RocCurveForDatasets] | true | List of ROC curve data for datasets. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). |
RocCurveResponse
{
"auc": 0,
"kolmogorovSmirnovMetric": 0,
"negativeClassPredictions": [
0
],
"positiveClassPredictions": [
0
],
"rocPoints": [
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
]
}
Roc curve data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
auc | number¦null | true | AUC value | |
kolmogorovSmirnovMetric | number¦null | true | Kolmogorov-Smirnov metric value | |
negativeClassPredictions | [number] | true | List of example predictions for the negative class. | |
positiveClassPredictions | [number] | true | List of example predictions for the positive class. | |
rocPoints | [RocPointsResponse] | true | The ROC curve data for that source, as specified below. |
RocPointsResponse
{
"accuracy": 0,
"f1Score": 0,
"falseNegativeScore": 0,
"falsePositiveRate": 0,
"falsePositiveScore": 0,
"fractionPredictedAsNegative": 0,
"fractionPredictedAsPositive": 0,
"liftNegative": 0,
"liftPositive": 0,
"matthewsCorrelationCoefficient": 0,
"negativePredictiveValue": 0,
"positivePredictiveValue": 0,
"threshold": 0,
"trueNegativeRate": 0,
"trueNegativeScore": 0,
"truePositiveRate": 0,
"truePositiveScore": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
accuracy | number | true | Accuracy for given threshold. | |
f1Score | number | true | F1 score. | |
falseNegativeScore | integer | true | False negative score. | |
falsePositiveRate | number | true | False positive rate. | |
falsePositiveScore | integer | true | False positive score. | |
fractionPredictedAsNegative | number | true | Fraction of data that will be predicted as negative. | |
fractionPredictedAsPositive | number | true | Fraction of data that will be predicted as positive. | |
liftNegative | number | true | Lift for the negative class. | |
liftPositive | number | true | Lift for the positive class. | |
matthewsCorrelationCoefficient | number | true | Matthews correlation coefficient. | |
negativePredictiveValue | number | true | Negative predictive value. | |
positivePredictiveValue | number | true | Positive predictive value. | |
threshold | number | true | Value of threshold for this ROC point. | |
trueNegativeRate | number | true | True negative rate. | |
trueNegativeScore | integer | true | True negative score. | |
truePositiveRate | number | true | True positive rate. | |
truePositiveScore | integer | true | True positive score. |
SeriesAccuracyCompute
{
"computeAllSeries": false
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
computeAllSeries | boolean | false | Indicates whether to calculate accuracy for all series or only first 1000 (sorted by name). |
SeriesAccuracyRetrieveDataResponse
{
"backtestingScore": 0,
"cluster": "string",
"duration": "string",
"endDate": "2019-08-24T14:15:22Z",
"holdoutScore": 0,
"multiseriesId": "string",
"multiseriesValues": [
"string"
],
"rowCount": 0,
"startDate": "2019-08-24T14:15:22Z",
"targetAverage": "string",
"validationScore": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
backtestingScore | number¦null | true | The backtesting score for this series. If backtesting has not been run for this model, this score will be null. | |
cluster | string¦null | false | The cluster associated with this series. | |
duration | string(duration) | true | The duration of this series formatted as an ISO 8601 duration string. | |
endDate | string(date-time)¦null | false | The ISO-formatted end date of this series. | |
holdoutScore | number¦null | false | The holdout set score for this series. If holdout is locked for the project, this score will be null. | |
multiseriesId | string | true | A DataRobot-generated ID corresponding to a single series in a multiseries dataset. | |
multiseriesValues | [string] | true | The actual values of series ID columns from the dataset. | |
rowCount | integer | true | The number of rows available for this series in the input dataset. | |
startDate | string(date-time)¦null | false | The ISO-formatted start date of this series. | |
targetAverage | any | false | For regression projects, this is the average (mean) value of target values for this series.For classification projects, this is the ratio of the positive class in the target for this series. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | number | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
validationScore | number¦null | true | The validation set score for this series |
SeriesAccuracyRetrieveResponse
{
"data": [
{
"backtestingScore": 0,
"cluster": "string",
"duration": "string",
"endDate": "2019-08-24T14:15:22Z",
"holdoutScore": 0,
"multiseriesId": "string",
"multiseriesValues": [
"string"
],
"rowCount": 0,
"startDate": "2019-08-24T14:15:22Z",
"targetAverage": "string",
"validationScore": 0
}
],
"next": "string",
"previous": "string",
"querySeriesCount": 0,
"totalSeriesCount": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
data | [SeriesAccuracyRetrieveDataResponse] | true | An array of available multiseries identifiers and column values. | |
next | string¦null | false | A URL pointing to the next page (if null, there is no next page). | |
previous | string¦null | false | A URL pointing to the previous page (if null, there is no previous page). | |
querySeriesCount | integer | true | The total number of series after filtering is applied. | |
totalSeriesCount | integer | true | The total number of series in the project dataset. |
ShapDistributionsData
{
"features": [
{
"feature": "string",
"featureType": "T",
"impactNormalized": 1,
"impactUnnormalized": 0,
"shapValues": [
{
"featureRank": 0,
"featureValue": 0,
"predictionValue": 0,
"rowIndex": 0,
"shapValue": 0
}
]
}
],
"totalFeaturesCount": 0
}
SHAP distributions data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
features | [ShapDistributionsRow] | true | maxItems: 100 |
List of SHAP distributions for each requested row. |
totalFeaturesCount | integer | true | The total number of features. |
ShapDistributionsRow
{
"feature": "string",
"featureType": "T",
"impactNormalized": 1,
"impactUnnormalized": 0,
"shapValues": [
{
"featureRank": 0,
"featureValue": 0,
"predictionValue": 0,
"rowIndex": 0,
"shapValue": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
feature | string | true | The feature name in the dataset. | |
featureType | string | true | Feature type. | |
impactNormalized | number | true | maximum: 1 |
The same as impactUnnormalized , but normalized such that the highest value is 1 . |
impactUnnormalized | number | true | How much worse the error metric score is when making predictions on modified data. | |
shapValues | [ShapDistributionsValue] | true | maxItems: 1000 |
The SHAP distributions values for this row. |
Enumerated Values¶
Property | Value |
---|---|
featureType | [T , X , B , C , CI , N , D , DD , FD , Q , CD , GEO , MC , INT , DOC ] |
ShapDistributionsValue
{
"featureRank": 0,
"featureValue": 0,
"predictionValue": 0,
"rowIndex": 0,
"shapValue": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureRank | integer | true | minimum: 0 (exclusive) |
The SHAP value rank of the feature for this row. |
featureValue | any | true | The value of the feature for this row. |
anyOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | number | false | none |
or
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
continued
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
predictionValue | number | true | The prediction value for this row. | |
rowIndex | integer¦null | true | minimum: 0 |
The index of this row. |
shapValue | number | true | The SHAP value of the feature for this row. |
ShapExplanationResponse
{
"feature": "string",
"featureValue": "string",
"strength": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
feature | string | true | Feature name | |
featureValue | string | true | Feature value for this row. First 50 characters are returned. | |
strength | number | true | Shapley value for this feature and row. |
ShapImpactData
{
"baseValue": [
0
],
"link": "string",
"quickCompute": true,
"rowCount": 0,
"shapImpacts": [
{
"featureName": "string",
"impactNormalized": 0,
"impactUnnormalized": 0
}
]
}
SHAP impact data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
baseValue | [number] | true | Mean of raw model predictions for the training data. | |
link | string¦null | true | Link function used to connect the SHAP importance values to the model output. | |
quickCompute | boolean | false | When enabled, limits the rows used from the selected source subset by default. When disabled, all rows are used. | |
rowCount | integer¦null | true | (Deprecated) The number of rows used to calculate SHAP impact. If rowCount is not specified, the value returned is null . |
|
shapImpacts | [ShapImpactEntity] | true | A list that contains SHAP impact scores. |
ShapImpactEntity
{
"featureName": "string",
"impactNormalized": 0,
"impactUnnormalized": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureName | string | true | The feature name in the dataset. | |
impactNormalized | number¦null | true | The normalized impact score value. | |
impactUnnormalized | number | true | The raw impact score value. |
ShapImpactRetrieveResponse
{
"count": 0,
"rowCount": 0,
"shapImpacts": [
{
"featureName": "string",
"impactNormalized": 0,
"impactUnnormalized": 0
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | true | The number of shapImpact object returned | |
rowCount | integer | false | The number of rows from dataset to use. | |
shapImpacts | [ShapImpactsResponse] | true | maxItems: 1000 minItems: 1 |
A list which contains shap impact scores for top 1000 features used by a model |
ShapImpactsResponse
{
"featureName": "string",
"impactNormalized": 0,
"impactUnnormalized": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureName | string | true | The feature name in dataset | |
impactNormalized | number | true | The normalized impact score value (largest value is 1) | |
impactUnnormalized | number | true | The raw impact score value |
ShapMatrixData
{
"baseValue": [
0
],
"colnames": [
"string"
],
"linkFunction": "string",
"matrix": [
[
0
]
],
"rowIndex": [
0
],
"timeSeriesRowIndex": [
[
0
]
]
}
SHAP matrix data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
baseValue | [number] | true | The mean of the raw model predictions for the training data. | |
colnames | [string] | true | The names of each column in the SHAP matrix. | |
linkFunction | string¦null | true | The link function used to connect the feature importance values to the model output. | |
matrix | [array] | true | SHAP matrix values. | |
rowIndex | [integer]¦null | true | The index of the data row used to compute the SHAP matrix. Not used in time-aware projects. | |
timeSeriesRowIndex | [array]¦null | false | An index composed of the timestamp, series id and forecast distance. Only used in time-aware projects. |
oneOf
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | integer | false | none |
xor
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
» anonymous | string | false | none |
ShapMatrixListDataField
{
"datasetId": "string",
"id": "string",
"metadata": {
"maxNormalizedMismatch": 0,
"mismatchRowCount": 0
},
"modelId": "string",
"projectId": "string",
"url": "http://example.com"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
datasetId | string | true | The dataset ID. | |
id | string | true | The ID of the SHAP matrix record. | |
metadata | ShapMatrixMetadataField | true | The metadata containing SHAP matrix calculation details. | |
modelId | string | true | The model ID. | |
projectId | string | true | The project ID. | |
url | string(uri) | true | The url at which you can retrieve the SHAP matrix. |
ShapMatrixListResponse
{
"count": 0,
"data": [
{
"datasetId": "string",
"id": "string",
"metadata": {
"maxNormalizedMismatch": 0,
"mismatchRowCount": 0
},
"modelId": "string",
"projectId": "string",
"url": "http://example.com"
}
],
"next": "http://example.com",
"previous": "http://example.com"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
count | integer | false | Number of items returned on this page. | |
data | [ShapMatrixListDataField] | true | Array of SHAP matrix scores records. | |
next | string(uri)¦null | true | URL pointing to the next page (if null, there is no next page). | |
previous | string(uri)¦null | true | URL pointing to the previous page (if null, there is no previous page). |
ShapMatrixMetadataField
{
"maxNormalizedMismatch": 0,
"mismatchRowCount": 0
}
The metadata containing SHAP matrix calculation details.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
maxNormalizedMismatch | number | false | The maximal relative normalized mismatch value. | |
mismatchRowCount | integer | false | The count of rows for which additivity check failed. |
ShapMatrixRetrieveResponse
{
"columnNames": [
"string"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
columnNames | [string] | true | The column names for corresponding dataset & their SHAP values. |
ShapPreviewData
{
"previews": [
{
"predictionValue": 0,
"previewValues": [
{
"featureName": "string",
"featureRank": 0,
"featureValue": "string",
"hasTextExplanations": true,
"isImage": true,
"shapValue": 0,
"textExplanations": [
"string"
]
}
],
"rowIndex": 0,
"totalPreviewFeatures": 0
}
],
"previewsCount": 0
}
SHAP preview data.
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
previews | [ShapPreviewRow] | true | List of SHAP previews for each requested row. | |
previewsCount | integer | true | The total number of previews. |
ShapPreviewRow
{
"predictionValue": 0,
"previewValues": [
{
"featureName": "string",
"featureRank": 0,
"featureValue": "string",
"hasTextExplanations": true,
"isImage": true,
"shapValue": 0,
"textExplanations": [
"string"
]
}
],
"rowIndex": 0,
"totalPreviewFeatures": 0
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
predictionValue | number | true | The prediction value for this row. | |
previewValues | [ShapPreviewValue] | true | The SHAP preview values for this row. | |
rowIndex | integer¦null | true | minimum: 0 |
The index of this row. |
totalPreviewFeatures | integer | true | minimum: 0 |
The total number of features available after name filters have been applied. |
ShapPreviewValue
{
"featureName": "string",
"featureRank": 0,
"featureValue": "string",
"hasTextExplanations": true,
"isImage": true,
"shapValue": 0,
"textExplanations": [
"string"
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureName | string | true | The name of the feature. | |
featureRank | integer | true | minimum: 0 (exclusive) |
The SHAP value rank of the feature for this row. |
featureValue | string | true | The value of the feature for this row. | |
hasTextExplanations | boolean | true | Whether the feature has text explanations available for this row. | |
isImage | boolean | false | Whether the feature is an image or not. | |
shapValue | number | true | The SHAP value of the feature for this row. | |
textExplanations | [string] | true | List of the text explanations for the feature for this row. |
Text
{
"allData": {
"missingRowsPercent": 100,
"perValueStatistics": [
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
]
},
"insightName": "importantNgrams",
"perCluster": [
{
"clusterName": "string",
"missingRowsPercent": 100,
"perValueStatistics": [
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
allData | AllDataText | true | Statistics for all data for different feature values. | |
insightName | string | true | Insight name. | |
perCluster | [PerClusterText] | true | Statistic values for different feature values in this cluster. |
Enumerated Values¶
Property | Value |
---|---|
insightName | importantNgrams |
TextFeature
{
"featureImpact": 0,
"featureName": "string",
"featureType": "text",
"insights": [
{
"allData": {
"missingRowsPercent": 100,
"perValueStatistics": [
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
]
},
"insightName": "importantNgrams",
"perCluster": [
{
"clusterName": "string",
"missingRowsPercent": 100,
"perValueStatistics": [
{
"contextualExtracts": [
"string"
],
"importance": 0,
"ngram": "string"
}
]
}
]
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
featureImpact | number¦null | false | Feature Impact score. | |
featureName | string | true | Feature name. | |
featureType | string | true | Feature Type. | |
insights | [Text] | true | A list of Cluster Insights for a feature. |
Enumerated Values¶
Property | Value |
---|---|
featureType | text |
WordCloudNgram
{
"class": "string",
"coefficient": -1,
"count": 0,
"frequency": 0,
"isStopword": true,
"ngram": "string",
"variable": "string"
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
class | string¦null | false | For classification - values of the target class for corresponding word or ngram. For regression - null. | |
coefficient | number | true | maximum: 1 minimum: -1 |
Describes effect of this ngram on the target. A large negative value means a strong effect toward the negative class in classification projects and a smaller predicted target value in regression projects. A large positive value means a strong effect toward the positive class and a larger predicted target value respectively. |
count | integer | true | Number of rows in the training sample where this ngram appears. | |
frequency | number | true | maximum: 1 minimum: 0 (exclusive) |
Frequency of this ngram relative to the most common ngram. |
isStopword | boolean | true | True for ngrams that DataRobot evaluates as stopwords. | |
ngram | string | true | Word or ngram value. | |
variable | string | true | String representation of the ngram source - contains column name and, for some models, preprocessing details. E.g. NGRAM_OCCUR_L2_colname will be for ngram occurrences count using L2 normalization from the colname column. |
WordCloudRetrieveResponse
{
"ngrams": [
{
"class": "string",
"coefficient": -1,
"count": 0,
"frequency": 0,
"isStopword": true,
"ngram": "string",
"variable": "string"
}
]
}
Properties¶
Name | Type | Required | Restrictions | Description |
---|---|---|---|---|
ngrams | [WordCloudNgram] | true | A list of dictionaries containing information about the most important ngrams. |