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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}"

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}"

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}"

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 insight 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}"

Body parameter

{
  "dataSliceId": "string",
  "entityId": "string",
  "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 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 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}"

Body parameter

{
  "dataSliceId": "string",
  "entityId": "string",
  "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 "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 ID of the Model

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]

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}"

Body parameter

{
  "dataSliceId": "string",
  "entityId": "string",
  "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 "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 ID of the external dataset
entityId path string true ID of the Model

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]

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}"

Body parameter

{
  "dataSliceId": "string",
  "entityId": "string",
  "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 "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 ID of the external dataset
entityId path string true ID of the Model

Enumerated Values

Parameter Value
source [validation, crossValidation, holdout, externalTestSet]
unslicedOnly [false, False, true, True]

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}"

Body parameter

{
  "dataSliceId": "string",
  "entityId": "string",
  "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 "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 ID of the external dataset
entityId path string true ID of the Model

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]

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

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/ 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/ 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}"

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/ 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/ 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}"

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/ 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/ 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 "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

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 "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

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}"

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": } where 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}"

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 "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

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}"

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}"

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:) ().csv").
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}"

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}"

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}"

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}"

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

Status Meaning Description Schema
200 OK Retrieve a CSV file of the raw data displayed with the anomaly score from the model. None
404 Not Found project Id / model Id does not exist or 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}/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}"

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__.csv").

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}"

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//models//datasetMulticlassLiftCharts/.

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}"

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": , "jobId": } where 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}/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}"

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}"

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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        ]
      },
      {
        "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",
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      {
        "name": "accuracy",
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      },
      {
        "name": "accuracy",
        "numLabelsUsedInCalculation": 0,
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      },
      {
        "name": "accuracy",
        "numLabelsUsedInCalculation": 0,
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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}"

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

DELETE /api/v2/projects/{projectId}/models/{modelId}/predictionExplanationsInitialization/

Delete an existing PredictionExplanationsInitialization.

Code samples

# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/predictionExplanationsInitialization/ \
  -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

Responses

Status Meaning Description Schema
204 No Content The deletion was successful. 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}/predictionExplanationsInitialization/

Retrieve the current PredictionExplanationsInitialization. A PredictionExplanationsInitialization is a pre-requisite for successfully computing prediction explanations using a particular model, and can be used to preview the prediction explanations that would be generated for a complete dataset.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/predictionExplanationsInitialization/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}"

Body parameter

{
  "modelId": "string",
  "predictionExplanationsSample": [
    {
      "adjustedPrediction": 0,
      "adjustedPredictionValues": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "forecastDistance": 0,
      "forecastPoint": "string",
      "prediction": 0,
      "predictionExplanations": [
        {
          "feature": "string",
          "featureValue": "string",
          "imageExplanationUrl": "string",
          "label": "string",
          "perNgramTextExplanations": [
            {
              "isUnknown": true,
              "ngrams": [
                {
                  "label": "string",
                  "value": 0
                }
              ],
              "qualitativateStrength": "string",
              "strength": 0
            }
          ],
          "qualitativateStrength": "string",
          "strength": 0
        }
      ],
      "predictionThreshold": 0,
      "predictionValues": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "rowId": 0,
      "seriesId": "string",
      "timestamp": "string"
    }
  ],
  "projectId": "string"
}

Parameters

Name In Type Required Description
excludeAdjustedPredictions query string false Whether to include adjusted prediction in the PredictionExplanationsSample response.
projectId path string true The project ID
modelId path string true The model ID
body body PredictionExplanationsInitializationRetrieve false none

Enumerated Values

Parameter Value
excludeAdjustedPredictions [false, False, true, True]

Responses

Status Meaning Description Schema
200 OK none 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}/predictionExplanationsInitialization/

Create a new prediction explanations initialization. This is a necessary prerequisite for generating prediction explanations.

Code samples

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/predictionExplanationsInitialization/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}"

Body parameter

{
  "maxExplanations": 3,
  "thresholdHigh": null,
  "thresholdLow": null
}

Parameters

Name In Type Required Description
projectId path string true The project ID
modelId path string true The model ID
body body PredictionExplanationsInitializationCreate false none

Responses

Status Meaning Description Schema
202 Accepted The request was accepted and will be worked on. 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}/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 value of impact indicate more important feature.

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 a Shap based Feature Impact with a model.

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}"

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}"

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}"

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

POST /api/v2/projects/{projectId}/predictionExplanations/

Create a new PredictionExplanations object (and its accompanying PredictionExplanationsRecord). In order to successfully create PredictionExplanations for a particular model and dataset, you must first - Compute feature impact for the model via POST /api/v2/projects/{projectId}/models/{modelId}/featureImpact/ - Compute a PredictionExplanationsInitialization for the model via POST /api/v2/projects/{projectId}/models/{modelId}/predictionExplanationsInitialization/ - Compute predictions for the model and dataset via POST /api/v2/projects/{projectId}/predictions/ thresholdHigh and thresholdLow are optional filters applied to speed up computation. When at least one is specified, only the selected outlier rows will have prediction explanations computed. Rows are considered to be outliers if their predicted value (in case of regression projects) or probability of being the positive class (in case of classification projects) isless than thresholdLow or greater than thresholdHigh. If neither is specified, prediction explanations will be computed for all rows.

Code samples

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/predictionExplanations/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}"

Body parameter

{
  "classNames": [
    "string"
  ],
  "datasetId": "string",
  "maxExplanations": 3,
  "modelId": "string",
  "numTopClasses": 1,
  "thresholdHigh": null,
  "thresholdLow": null
}

Parameters

Name In Type Required Description
projectId path string true The project ID
body body PredictionExplanationsCreate false none

Responses

Status Meaning Description Schema
202 Accepted The request was accepted and will be worked on. 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}/predictionExplanations/{predictionExplanationsId}/

Retrieve stored Prediction Explanations. Each PredictionExplanationsRow retrieved corresponds to a row of the prediction dataset, although some rows may not have had prediction explanations computed depending on the thresholds selected.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/predictionExplanations/{predictionExplanationsId}/?limit=3000 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
offset query integer false This many results will be skipped.
limit query integer true At most this many results are returned. The default may change and a new maximum limit may be imposed without notice.
excludeAdjustedPredictions query string false Whether to include adjusted prediction in PredictionExplanationsRow response.
projectId path string true The project ID
predictionExplanationsId path string true The ID of the PredictionExplanationsRecord to retrieve.

Enumerated Values

Parameter Value
excludeAdjustedPredictions [false, False, true, True]

Example responses

200 Response

{
  "adjustmentMethod": "string",
  "count": 0,
  "data": [
    {
      "adjustedPrediction": 0,
      "adjustedPredictionValues": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "forecastDistance": 0,
      "forecastPoint": "string",
      "prediction": 0,
      "predictionExplanations": [
        {
          "feature": "string",
          "featureValue": "string",
          "imageExplanationUrl": "string",
          "label": "string",
          "perNgramTextExplanations": [
            {
              "isUnknown": true,
              "ngrams": [
                {
                  "label": "string",
                  "value": 0
                }
              ],
              "qualitativateStrength": "string",
              "strength": 0
            }
          ],
          "qualitativateStrength": "string",
          "strength": 0
        }
      ],
      "predictionThreshold": 0,
      "predictionValues": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "rowId": 0,
      "seriesId": "string",
      "timestamp": "string"
    }
  ],
  "id": "string",
  "next": "http://example.com",
  "predictionExplanationsRecordLocation": "string",
  "previous": "http://example.com"
}

Responses

Status Meaning Description Schema
200 OK none PredictionExplanationsRetrieve

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/predictionExplanationsRecords/

List PredictionExplanationsRecord objects for a project. These contain metadata about the computed prediction explanations and the location at which the PredictionExplanations can be retrieved.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/predictionExplanationsRecords/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
offset query integer false This many results will be skipped.
limit query integer false At most this many results are returned.
modelId query string false If specified, only prediction explanations records computed for this model will be returned.
projectId path string true The project ID

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "datasetId": "string",
      "finishTime": 0,
      "id": "string",
      "maxExplanations": 0,
      "modelId": "string",
      "numColumns": 0,
      "predictionExplanationsLocation": "string",
      "predictionThreshold": 0,
      "projectId": "string",
      "thresholdHigh": 0,
      "thresholdLow": 0
    }
  ],
  "next": "string",
  "previous": "string"
}

Responses

Status Meaning Description Schema
200 OK The object was found and returned successfully. PredictionExplanationsRecordList

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

DELETE /api/v2/projects/{projectId}/predictionExplanationsRecords/{predictionExplanationsId}/

Delete saved Prediction Explanations. Deletes both the actual prediction explanations and the corresponding PredictionExplanationsRecord.

Code samples

# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/projects/{projectId}/predictionExplanationsRecords/{predictionExplanationsId}/ \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
projectId path string true The project ID
predictionExplanationsId path string true The ID of the PredictionExplanationsRecord to retrieve.

Responses

Status Meaning Description Schema
204 No Content The object was deleted successfully. None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/predictionExplanationsRecords/{predictionExplanationsId}/

Retrieve a PredictionExplanationsRecord object. A PredictionExplanationsRecord contains metadata about the computed prediction explanations and the location at which the PredictionExplanations can be retrieved.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/predictionExplanationsRecords/{predictionExplanationsId}/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}"

Body parameter

{
  "datasetId": "string",
  "finishTime": 0,
  "id": "string",
  "maxExplanations": 0,
  "modelId": "string",
  "numColumns": 0,
  "predictionExplanationsLocation": "string",
  "predictionThreshold": 0,
  "projectId": "string",
  "thresholdHigh": 0,
  "thresholdLow": 0
}

Parameters

Name In Type Required Description
projectId path string true The project ID
predictionExplanationsId path string true The ID of the PredictionExplanationsRecord to retrieve.
body body PredictionExplanationsRecord false none

Responses

Status Meaning Description Schema
200 OK The object was found and returned successfully. None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/shapMatrices/

Get a list of available SHAP matrix records.

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.

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}"

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}/

Get matrix with SHAP prediction explanations scores.

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"
}

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
}

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 Metadata information for holdout.
holdoutStatuses AccuracyOverTimePlotsStatus true Status information for holdout.
resolutions [string] true maxItems: 9
minItems: 1
An array of available time resolutions for which plots can be retrieved.

AccuracyOverTimePlotsStatistics

{
  "durbinWatson": 4
}

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
}

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"
    }
  ]
}

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 Metadata information for holdout.
holdoutStatuses AccuracyOverTimePlotsStatus true Status information for holdout.
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,
      "values": [
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
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    },
    {
      "name": "accuracy",
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      "values": [
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    },
    {
      "name": "accuracy",
      "numLabelsUsedInCalculation": 0,
      "values": [
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    },
    {
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    },
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    }
  ],
  "source": "validation",
  "thresholds": [
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}

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": [
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  ]
}

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",
  "externalDatasetId": "string",
  "source": "validation"
}

Properties

Name Type Required Restrictions Description
dataSliceId string false ID of the Data Slice
entityId string true ID of the entity.
externalDatasetId string false ID of the external dataset
source string true 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]

ComputeFeatureImpactRequest

{
  "dataSliceId": "string",
  "entityId": "string",
  "externalDatasetId": "string",
  "rowCount": 10,
  "source": "training"
}

Properties

Name Type Required Restrictions Description
dataSliceId string false ID of the Data Slice
entityId string true ID of the entity.
externalDatasetId string false ID of the external dataset
rowCount integer true maximum: 100000
minimum: 10
Number of rows to use to calculate feature impact.
source string true The subset of data used to compute the insight.

Enumerated Values

Property 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]

ComputeInsightsResponse

{
  "qid": 0
}

Properties

Name Type Required Restrictions Description
qid integer¦null true The QID of the job that computes insights request.

ComputeLiftChartRequest

{
  "dataSliceId": "string",
  "entityId": "string",
  "externalDatasetId": "string",
  "source": "validation"
}

Properties

Name Type Required Restrictions Description
dataSliceId string false ID of the Data Slice
entityId string true ID of the entity.
externalDatasetId string false ID of the external dataset
source string true The subset of data used to compute the insight.

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]

ComputeResidualsRequest

{
  "dataSliceId": "string",
  "entityId": "string",
  "externalDatasetId": "string",
  "source": "validation"
}

Properties

Name Type Required Restrictions Description
dataSliceId string false ID of the Data Slice
entityId string true ID of the entity.
externalDatasetId string false ID of the external dataset
source string true The subset of data used to compute the insight.

Enumerated Values

Property Value
source [validation, crossValidation, holdout]

ComputeRocCurveRequest

{
  "dataSliceId": "string",
  "entityId": "string",
  "externalDatasetId": "string",
  "source": "validation"
}

Properties

Name Type Required Restrictions Description
dataSliceId string false ID of the Data Slice
entityId string true ID of the entity.
externalDatasetId string false ID of the external dataset
source string true The subset of data used to compute the insight.

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]

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"
  ]
}

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"
    }
  ]
}

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 validation.

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"
}

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"
}

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"
    }
  ]
}

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
}

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
  ]
}

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 Metadata information for holdout.
holdoutStatuses ForecastVsActualPlotsStatus true Status information for holdout.
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 validation.

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"
}

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

Name Type Required Restrictions Description
count integer true Total num of samples located within this geometry.

GeoFeaturePlotSummary

{
  "maxCount": 0,
  "minCount": 0,
  "totalCount": 0
}

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"
}

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
}

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

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      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1,
      1
    ]
  },
  "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
    }
  ]
}

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
}

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
  }
}

Properties

Name Type Required Restrictions Description
crossValidation ModelResidualsChartData false Chart data from the cross validation data source
holdout ModelResidualsChartData false Chart data from the holdout 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
    }
  ]
}

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/ 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/ 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
}

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.

PerNgramTextExplanations

{
  "isUnknown": true,
  "ngrams": [
    {
      "label": "string",
      "value": 0
    }
  ],
  "qualitativateStrength": "string",
  "strength": 0
}

Properties

Name Type Required Restrictions Description
isUnknown boolean true Whether the ngram is identifiable by the blueprint or not.
ngrams [PredictionExplanationsPredictionValues] true maxItems: 1000
List of JSON objects with the ngram starting index, ngram ending index and unknown ngram information.
qualitativateStrength string true A human-readable description of how strongly these ngrams's affected the prediction(e.g. '+++', '--', '+', '<+', '<-').
strength number true The amount these ngrams's affected the prediction.

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
    }
  ]
}

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
    }
  ]
}

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.

PredictionExplanation

{
  "feature": "string",
  "featureValue": "string",
  "imageExplanationUrl": "string",
  "label": "string",
  "perNgramTextExplanations": [
    {
      "isUnknown": true,
      "ngrams": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "qualitativateStrength": "string",
      "strength": 0
    }
  ],
  "qualitativateStrength": "string",
  "strength": 0
}

Properties

Name Type Required Restrictions Description
feature string true The name of the feature contributing to the prediction.
featureValue string true The value the feature took on for this row. For image features, this value is the URL of the input image (New in v2.21).
imageExplanationUrl string¦null true For image features, the URL of the image containing the input image overlaid by the activation heatmap. For non-image features, this field is null.
label string true Describes what this model output corresponds to. For regression projects, it is the name of the target feature. For classification projects, it is a level from the target feature. For Anomaly Detection models it is an Anomaly Score.
perNgramTextExplanations [PerNgramTextExplanations] false maxItems: 10000
For text features, an array of JSON object containing the per ngram based text prediction explanations.
qualitativateStrength string true A human-readable description of how strongly the feature affected the prediction (e.g. '+++', '--', '+', '<+', '<-').
strength number true The amount this feature's value affected the prediction.

PredictionExplanationsCreate

{
  "classNames": [
    "string"
  ],
  "datasetId": "string",
  "maxExplanations": 3,
  "modelId": "string",
  "numTopClasses": 1,
  "thresholdHigh": null,
  "thresholdLow": null
}

Properties

Name Type Required Restrictions Description
classNames [string] false maxItems: 10
List of class names that will be explained for each row for multiclass. Mutually exclusive with numTopClasses. If neither specified - we assume numTopClasses=1.
datasetId string true The dataset ID.
maxExplanations integer false maximum: 10
minimum: 0
The maximum number of prediction explanations to supply per row of the dataset.
modelId string true The model ID.
numTopClasses integer false maximum: 10
minimum: 1
Number of top predicted classes for each row that will be explained for multiclass. Mutually exclusive with classNames. If neither specified - we assume numTopClasses=1.
thresholdHigh number¦null false The high threshold, above which a prediction must score in order for prediction explanations to be computed. If neither thresholdHigh nor thresholdLow is specified, prediction explanations will be computed for all rows.
thresholdLow number¦null false The lower threshold, below which a prediction must score in order for prediction explanations to be computed for a row in the dataset. If neither thresholdHigh nor thresholdLow is specified, prediction explanations will be computed for all rows.

PredictionExplanationsInitializationCreate

{
  "maxExplanations": 3,
  "thresholdHigh": null,
  "thresholdLow": null
}

Properties

Name Type Required Restrictions Description
maxExplanations integer false maximum: 10
minimum: 1
The maximum number of prediction explanations to supply per row of the dataset.
thresholdHigh number¦null false The high threshold, above which a prediction must score in order for prediction explanations to be computed. If neither thresholdHigh nor thresholdLow is specified, prediction explanations will be computed for all rows.
thresholdLow number¦null false The lower threshold, below which a prediction must score in order for prediction explanations to be computed for a row in the dataset. If neither thresholdHigh nor thresholdLow is specified, prediction explanations will be computed for all rows.

PredictionExplanationsInitializationRetrieve

{
  "modelId": "string",
  "predictionExplanationsSample": [
    {
      "adjustedPrediction": 0,
      "adjustedPredictionValues": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "forecastDistance": 0,
      "forecastPoint": "string",
      "prediction": 0,
      "predictionExplanations": [
        {
          "feature": "string",
          "featureValue": "string",
          "imageExplanationUrl": "string",
          "label": "string",
          "perNgramTextExplanations": [
            {
              "isUnknown": true,
              "ngrams": [
                {
                  "label": "string",
                  "value": 0
                }
              ],
              "qualitativateStrength": "string",
              "strength": 0
            }
          ],
          "qualitativateStrength": "string",
          "strength": 0
        }
      ],
      "predictionThreshold": 0,
      "predictionValues": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "rowId": 0,
      "seriesId": "string",
      "timestamp": "string"
    }
  ],
  "projectId": "string"
}

Properties

Name Type Required Restrictions Description
modelId string true The model ID.
predictionExplanationsSample [PredictionExplanationsRow] true Each is a PredictionExplanationsRow. They represent a small sample of prediction explanations that could be generated for a particular dataset. They will have the same schema as the data array in the response from GET /api/v2/projects/{projectId}/predictionExplanations/{predictionExplanationsId}/. As of v2.21 only difference is that there is no forecastPoint in response for time series projects.
projectId string true The project ID.

PredictionExplanationsPredictionValues

{
  "label": "string",
  "value": 0
}

Properties

Name Type Required Restrictions Description
label string true Describes what this model output corresponds to. For regression projects, it is the name of the target feature. For classification projects, it is a level from the target feature. For Anomaly Detection models it is an Anomaly Score.
value number true The output of the prediction. For regression projects, it is the predicted value of the target. For classification projects, it is the predicted probability the row belongs to the class identified by the label.

PredictionExplanationsRecord

{
  "datasetId": "string",
  "finishTime": 0,
  "id": "string",
  "maxExplanations": 0,
  "modelId": "string",
  "numColumns": 0,
  "predictionExplanationsLocation": "string",
  "predictionThreshold": 0,
  "projectId": "string",
  "thresholdHigh": 0,
  "thresholdLow": 0
}

Properties

Name Type Required Restrictions Description
datasetId string true The dataset ID.
finishTime number true Timestamp referencing when computation for these prediction explanations finished.
id string true The PredictionExplanationsRecord ID.
maxExplanations integer true The maximum number of codes generated per prediction.
modelId string true The model ID.
numColumns integer true The number of columns prediction explanations were computed for.
predictionExplanationsLocation string true Where to retrieve the prediction explanations.
predictionThreshold number¦null true The threshold value used for binary classification prediction.
projectId string true The project ID.
thresholdHigh number¦null true The prediction explanation high threshold. Predictions must be above this value (or below the thresholdLow value) to have PredictionExplanations computed.
thresholdLow number¦null true The prediction explanation low threshold. Predictions must be below this value (or above the thresholdHigh value) to have PredictionExplanations computed.

PredictionExplanationsRecordList

{
  "count": 0,
  "data": [
    {
      "datasetId": "string",
      "finishTime": 0,
      "id": "string",
      "maxExplanations": 0,
      "modelId": "string",
      "numColumns": 0,
      "predictionExplanationsLocation": "string",
      "predictionThreshold": 0,
      "projectId": "string",
      "thresholdHigh": 0,
      "thresholdLow": 0
    }
  ],
  "next": "string",
  "previous": "string"
}

Properties

Name Type Required Restrictions Description
count integer true minimum: 0
The number of items returned on this page.
data [PredictionExplanationsRecord] true Each has the same schema as if retrieving the prediction explanations individually from GET /api/v2/projects/{projectId}/predictionExplanationsRecords/{predictionExplanationsId}/.
next string¦null true A URL pointing to the next page (if null, there is no next page).
previous string¦null true A URL pointing to the previous page (if null, there is no previous page).

PredictionExplanationsRetrieve

{
  "adjustmentMethod": "string",
  "count": 0,
  "data": [
    {
      "adjustedPrediction": 0,
      "adjustedPredictionValues": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "forecastDistance": 0,
      "forecastPoint": "string",
      "prediction": 0,
      "predictionExplanations": [
        {
          "feature": "string",
          "featureValue": "string",
          "imageExplanationUrl": "string",
          "label": "string",
          "perNgramTextExplanations": [
            {
              "isUnknown": true,
              "ngrams": [
                {
                  "label": "string",
                  "value": 0
                }
              ],
              "qualitativateStrength": "string",
              "strength": 0
            }
          ],
          "qualitativateStrength": "string",
          "strength": 0
        }
      ],
      "predictionThreshold": 0,
      "predictionValues": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "rowId": 0,
      "seriesId": "string",
      "timestamp": "string"
    }
  ],
  "id": "string",
  "next": "http://example.com",
  "predictionExplanationsRecordLocation": "string",
  "previous": "http://example.com"
}

Properties

Name Type Required Restrictions Description
adjustmentMethod string true 'exposureNormalized' (for regression projects with exposure) or 'N/A' (for classification projects) The value of 'exposureNormalized' indicates that prediction outputs are adjusted (or divided) by exposure. The value of 'N/A' indicates that no adjustments are applied to the adjusted predictions and they are identical to the unadjusted predictions.
count integer true How many rows of prediction explanations were returned.
data [PredictionExplanationsRow] true Each is a PredictionExplanationsRow corresponding to one row of the prediction dataset.
id string true The ID of this group of prediction explanations.
next string(uri)¦null true URL pointing to the next page (if null, there is no next page).
predictionExplanationsRecordLocation string true The URL of the PredictionExplanationsRecord associated with these prediction explanations.
previous string(uri)¦null true URL pointing to the previous page (if null, there is no previous page).

PredictionExplanationsRow

{
  "adjustedPrediction": 0,
  "adjustedPredictionValues": [
    {
      "label": "string",
      "value": 0
    }
  ],
  "forecastDistance": 0,
  "forecastPoint": "string",
  "prediction": 0,
  "predictionExplanations": [
    {
      "feature": "string",
      "featureValue": "string",
      "imageExplanationUrl": "string",
      "label": "string",
      "perNgramTextExplanations": [
        {
          "isUnknown": true,
          "ngrams": [
            {
              "label": "string",
              "value": 0
            }
          ],
          "qualitativateStrength": "string",
          "strength": 0
        }
      ],
      "qualitativateStrength": "string",
      "strength": 0
    }
  ],
  "predictionThreshold": 0,
  "predictionValues": [
    {
      "label": "string",
      "value": 0
    }
  ],
  "rowId": 0,
  "seriesId": "string",
  "timestamp": "string"
}

Properties

Name Type Required Restrictions Description
adjustedPrediction number true The exposure-adjusted output of the model for this row.
adjustedPredictionValues [PredictionExplanationsPredictionValues] true The exposure-adjusted output of the model for this row.
forecastDistance integer true Forecast distance for the row. For time series projects only.
forecastPoint string true Forecast point for the row. For time series projects only.
prediction number true The output of the model for this row.
predictionExplanations [PredictionExplanation] true A list of prediction explanations.
predictionThreshold number¦null true The threshold value used for classification prediction.
predictionValues [PredictionExplanationsPredictionValues] true A list of prediction values.
rowId integer true Which row this PredictionExplanationsRow describes.
seriesId string¦null true The ID of the series value for the row in a multiseries project. For a single series project this will be null. For time series projects only.
timestamp string true Timestamp for the row. For time series projects only.

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 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 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 Residuals data.
dataSliceId string¦null false ID of the data slice.
entityId string false ID of the model.
externalDatasetId string¦null false 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 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.

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 The ROC curve data for that source, as specified below. Each point specifies how the model performed for a particular classification threshold.

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
    }
  ]
}

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.

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.

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

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
}

Properties

Name Type Required Restrictions Description
maxNormalizedMismatch number true The maximal relative normalized mismatch value.
mismatchRowCount integer true 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.

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.

更新しました April 24, 2024