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Models

This page outlines the operations, endpoints, parameters, and example requests and responses for the Models.

GET /api/v2/customInferenceImages/{imageId}/featureImpact/

Retrieve feature impact scores for features in a custom inference model image.

.. minversion:: v2.23 DEPRECATED: please use version route instead: GET /api/v2/customModels/{customModelId}/versions/{customModelVersionId}/featureImpact/

This route is a counterpart of a corresponding endpoint for native models: GET /api/v2/projects/{projectId}/models/{modelId}/featureImpact/

Code samples

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

Parameters

Name In Type Required Description
imageId path string true ID of the image of the custom inference model to retrieve feature impact from.

Example responses

200 Response

{
  "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 Custom model feature impact returned. FeatureImpactResponse
404 Not Found No feature impact data found for custom model. None
422 Unprocessable Entity Cannot retrieve feature impact scores: (1) if custom model is not an inference model, (2) if training data is not assigned, (3) if feature impact job is in progress for custom model. None

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

BearerAuth

POST /api/v2/customInferenceImages/{imageId}/featureImpact/

Add a request to calculate feature impact for a custom inference model image to the queue.

.. minversion:: v2.23 DEPRECATED: please use version route instead: POST /api/v2/customModels/{customModelId}/versions/{customModelVersionId}/featureImpact/

This route is a counterpart of a corresponding endpoint for native models: POST /api/v2/projects/{projectId}/models/{modelId}/featureImpact/

Code samples

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

Body parameter

{
  "rowCount": 10
}

Parameters

Name In Type Required Description
imageId path string true ID of the image of the custom inference model to submit feature impact job for.
body body FeatureImpactCreatePayload false none

Example responses

202 Response

{
  "statusId": "string"
}

Responses

Status Meaning Description Schema
202 Accepted Feature impact request has been successfully submitted. FeatureImpactCreateResponse
404 Not Found If feature impact has already been submitted. The response will include jobId property which can be used for tracking its progress. None
422 Unprocessable Entity If job cannot be submitted because of invalid input or model state: (1) if image id does not correspond to a custom inference model, (2) if training data is not yet assigned or assignment is in progress, (3) if the rowCount exceeds the minimum or maximum value for this model's training data. None

Response Headers

Status Header Type Format Description
202 Location string Contains a url for tracking job status: GET /api/v2/status/{statusId}/.

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

BearerAuth

DELETE /api/v2/customModels/{customModelId}/versions/{customModelVersionId}/dependencyBuild/

Cancel the custom model version's dependency build.

Code samples

# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/customModels/{customModelId}/versions/{customModelVersionId}/dependencyBuild/ \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
customModelId path string true ID of the custom model.
customModelVersionId path string true ID of the custom model version.

Responses

Status Meaning Description Schema
204 No Content Custom model version's dependency build was cancelled. None
409 Conflict Custom model dependency build has reached a terminal state and cannot be cancelled. None
422 Unprocessable Entity No custom model dependency build started for specified version or dependency image is in use and cannot be deleted None

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

BearerAuth

GET /api/v2/customModels/{customModelId}/versions/{customModelVersionId}/dependencyBuild/

Retrieve the custom model version's dependency build status.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/customModels/{customModelId}/versions/{customModelVersionId}/dependencyBuild/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
customModelId path string true ID of the custom model.
customModelVersionId path string true ID of the custom model version.

Example responses

200 Response

{
  "buildEnd": "string",
  "buildLogLocation": "http://example.com",
  "buildStart": "string",
  "buildStatus": "submitted"
}

Responses

Status Meaning Description Schema
200 OK The metadata from the custom model version's dependency build. BaseDependencyBuildMetadataResponse
422 Unprocessable Entity Custom model dependency build has not started. None

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

BearerAuth

POST /api/v2/customModels/{customModelId}/versions/{customModelVersionId}/dependencyBuild/

Start a custom model version's dependency build. This is required to test, deploy, or train custom models.

Code samples

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/customModels/{customModelId}/versions/{customModelVersionId}/dependencyBuild/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
customModelId path string true ID of the custom model.
customModelVersionId path string true ID of the custom model version.

Example responses

202 Response

{
  "buildEnd": "string",
  "buildLogLocation": "http://example.com",
  "buildStart": "string",
  "buildStatus": "submitted"
}

Responses

Status Meaning Description Schema
202 Accepted Custom model version's dependency build has started. BaseDependencyBuildMetadataResponse
422 Unprocessable Entity Custom model dependency build has failed. None

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

BearerAuth

GET /api/v2/customModels/{customModelId}/versions/{customModelVersionId}/dependencyBuildLog/

Retrieve the custom model version's dependency build log.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/customModels/{customModelId}/versions/{customModelVersionId}/dependencyBuildLog/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
customModelId path string true ID of the custom model.
customModelVersionId path string true ID of the custom model version.

Example responses

200 Response

{
  "data": "string"
}

Responses

Status Meaning Description Schema
200 OK The log file generated during the custom model version's dependency build. DependencyBuildLogResponse
404 Not Found Dependency build is in progress or could not be found. None
422 Unprocessable Entity Custom model dependency build has not started. None

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

BearerAuth

GET /api/v2/customTrainingBlueprints/

List custom training blueprints.

This route retrieves the metadata for all custom training blueprints a user has access to.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/customTrainingBlueprints/?offset=0&limit=1000 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
offset query integer true This many results will be skipped.
limit query integer true At most this many results are returned.
customModelId query string false List blueprints for a specific model. Default: all.
reverse query string false List blueprints in reverse order.
targetTypes query array[string] false Custom model target types to return.

Enumerated Values

Parameter Value
reverse [false, False, true, True]
targetTypes [Binary, Regression, Multiclass, Anomaly, Transform, TextGeneration, Unstructured]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "createdAt": "string",
      "customModel": {
        "id": "string",
        "name": "string"
      },
      "customModelVersion": {
        "id": "string",
        "label": "string"
      },
      "executionEnvironment": {
        "id": "string",
        "name": "string"
      },
      "executionEnvironmentVersion": {
        "id": "string",
        "label": "string"
      },
      "targetType": "Binary",
      "trainingHistory": [
        {
          "creationDate": "string",
          "lid": "string",
          "pid": "string",
          "projectModelsCount": 0,
          "projectName": "string",
          "targetName": "string"
        }
      ],
      "userBlueprintId": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK Custom training blueprint list returned. CustomTrainingBlueprintListResponse

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

BearerAuth

POST /api/v2/customTrainingBlueprints/

This route creates a blueprint from a custom training estimator with an environment so that it can be trained via blueprint ID.

Code samples

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

Body parameter

{
  "customModelVersionId": "string"
}

Parameters

Name In Type Required Description
body body CustomTrainingBlueprintCreate false none

Example responses

201 Response

{
  "createdAt": "string",
  "customModel": {
    "id": "string",
    "name": "string"
  },
  "customModelVersion": {
    "id": "string",
    "label": "string"
  },
  "executionEnvironment": {
    "id": "string",
    "name": "string"
  },
  "executionEnvironmentVersion": {
    "id": "string",
    "label": "string"
  },
  "targetType": "Binary",
  "trainingHistory": [
    {
      "creationDate": "string",
      "lid": "string",
      "pid": "string",
      "projectModelsCount": 0,
      "projectName": "string",
      "targetName": "string"
    }
  ],
  "userBlueprintId": "string"
}

Responses

Status Meaning Description Schema
201 Created Blueprint successfully created. CustomTrainingBlueprintResponse
404 Not Found Any of the entities in the request cannot be retrieved. None
422 Unprocessable Entity Input parameters are invalid: either the custom model is for inference or no environment version ID was specified and the given environment has no versions. None

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

BearerAuth

GET /api/v2/executionEnvironments/{environmentId}/accessControl/

Get a list of users who have access to this execution environment and their roles.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/executionEnvironments/{environmentId}/accessControl/?offset=0&limit=0 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
offset query integer true This many results will be skipped
limit query integer true At most this many results are returned
username query string false Optional, only return the access control information for a user with this username.
userId query string false Optional, only return the access control information for a user with this user ID.
environmentId path string true The ID of the environment.

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "canShare": true,
      "role": "string",
      "userId": "string",
      "username": "string"
    }
  ],
  "next": "string",
  "previous": "string"
}

Responses

Status Meaning Description Schema
200 OK none SharingListResponse
400 Bad Request Bad Request. Both username and userId were specified None
403 Forbidden Forbidden. The user does not have permissions to view the execution environment access list. None
404 Not Found Execution environment not found. Either the execution environment does not exist or user does not have permission to view it. None

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

BearerAuth

PATCH /api/v2/executionEnvironments/{environmentId}/accessControl/

Grant access or update roles for users on this execution environment. Up to 100 user roles may be set in a single request.

Code samples

# You can also use wget
curl -X PATCH https://app.datarobot.com/api/v2/executionEnvironments/{environmentId}/accessControl/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}"

Body parameter

{
  "data": [
    {
      "canShare": true,
      "role": "ADMIN",
      "username": "string"
    }
  ]
}

Parameters

Name In Type Required Description
environmentId path string true The ID of the environment.
body body SharingUpdateOrRemoveWithGrant false none

Responses

Status Meaning Description Schema
200 OK none None
204 No Content Roles updated successfully. None
403 Forbidden User can view execution environment but does not have permission to grant these roles on the execution environment. None
404 Not Found Either the execution environment does not exist or the user does not have permissions to view the execution environment. None
409 Conflict The request would leave the execution environment without an owner. None
422 Unprocessable Entity One of the users in the request does not exist, or the request is otherwise invalid. None

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

BearerAuth

GET /api/v2/modelPackages/

Retrieve the list of model packages a user has access to.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/modelPackages/ \
  -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, limit results to model packages for the model with the specified ID.
similarTo query string false Return model packages similar to a given model package ID. If used, will only return model packages that match target.name, target.type, target.classNames (for classification models), modelKind.isTimeSeries, and modelKind.isMultiseries of the specified model package.
forChallenger query boolean false Can be used with similarTo to request similar model packages with the intent to use them as challenger models; for external model packages, instead of returning similar external model packages, similar DataRobot and Custom model packages will be retrieved.
search query string false Provide a term to search for in package name, model name, or description
predictionThreshold query number false Prediction threshold used for binary classification models
imported query boolean false If specified, filter for either imported (true) or non-imported (false) model packages
predictionEnvironmentId query string false Can be used to filter packages by what is supported by the prediction environment
modelKind query any false Return models from the registry that match a specific format.
buildStatus query string false If specified, filter model packages by the build status.

Enumerated Values

Parameter Value
buildStatus [inProgress, complete, failed]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "activeDeploymentCount": 0,
      "buildStatus": "inProgress",
      "capabilities": {
        "supportsAutomaticActuals": true,
        "supportsChallengerModels": true,
        "supportsFeatureDriftTracking": true,
        "supportsHumilityRecommendedRules": true,
        "supportsHumilityRules": true,
        "supportsHumilityRulesDefaultCalculations": true,
        "supportsPredictionWarning": true,
        "supportsRetraining": true,
        "supportsScoringCodeDownload": true,
        "supportsSecondaryDatasets": true,
        "supportsSegmentedAnalysisDriftAndAccuracy": true,
        "supportsShapBasedPredictionExplanations": true,
        "supportsTargetDriftTracking": true
      },
      "datasets": {
        "baselineSegmentedBy": [
          "string"
        ],
        "datasetName": "string",
        "holdoutDataCatalogId": "string",
        "holdoutDataCatalogVersionId": "string",
        "holdoutDatasetName": "string",
        "targetHistogramBaseline": "predictions",
        "trainingDataCatalogId": "string",
        "trainingDataCatalogVersionId": "string",
        "trainingDataSize": 0
      },
      "id": "string",
      "importMeta": {
        "containsFearPipeline": true,
        "containsFeaturelists": true,
        "containsLeaderboardMeta": true,
        "containsProjectMeta": true,
        "creatorFullName": "string",
        "creatorId": "string",
        "creatorUsername": "string",
        "dateCreated": "string",
        "originalFileName": "string"
      },
      "isArchived": true,
      "isDeprecated": true,
      "mlpkgFileContents": {
        "allTimeSeriesPredictionIntervals": true
      },
      "modelDescription": {
        "buildEnvironmentType": "DataRobot",
        "description": "string",
        "location": "string",
        "modelCreatedAt": "string",
        "modelCreatorEmail": "string",
        "modelCreatorId": null,
        "modelCreatorName": "string",
        "modelName": "string"
      },
      "modelExecutionType": "dedicated",
      "modelId": "string",
      "modelKind": {
        "isAnomalyDetectionModel": true,
        "isCombinedModel": true,
        "isDecisionFlow": true,
        "isFeatureDiscovery": true,
        "isMultiseries": true,
        "isTimeSeries": true,
        "isUnsupervisedLearning": true
      },
      "name": "string",
      "permissions": [
        "string"
      ],
      "sourceMeta": {
        "decisionFlowId": "string",
        "decisionFlowVersionId": "string",
        "environmentUrl": "http://example.com",
        "fips_140_2Enabled": true,
        "projectCreatedAt": "string",
        "projectCreatorEmail": "string",
        "projectCreatorId": null,
        "projectCreatorName": "string",
        "projectId": "string",
        "projectName": "string",
        "scoringCode": {
          "dataRobotPredictionVersion": "string",
          "location": "local_leaderboard"
        },
        "useCaseDetails": {
          "createdAt": "string",
          "creatorEmail": "string",
          "creatorId": "string",
          "creatorName": "string",
          "id": "string",
          "name": "string"
        }
      },
      "target": {
        "classCount": 0,
        "classNames": [
          "string"
        ],
        "name": "string",
        "predictionProbabilitiesColumn": "string",
        "predictionThreshold": 1,
        "type": "Binary"
      },
      "timeseries": {
        "datetimeColumnFormat": "string",
        "datetimeColumnName": "string",
        "effectiveFeatureDerivationWindowEnd": 0,
        "effectiveFeatureDerivationWindowStart": 0,
        "featureDerivationWindowEnd": 0,
        "featureDerivationWindowStart": 0,
        "forecastDistanceColumnName": "string",
        "forecastDistances": [
          0
        ],
        "forecastDistancesTimeUnit": "MICROSECOND",
        "forecastPointColumnName": "string",
        "isCrossSeries": true,
        "isNewSeriesSupport": true,
        "isTraditionalTimeSeries": true,
        "seriesColumnName": "string"
      },
      "updatedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "userProvidedId": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK none ModelPackageListResponse
400 Bad Request Request invalid, refer to messages for detail. None
403 Forbidden Either MMM Model Packages or New Model Registry are not enabled. None
404 Not Found User permissions problem. None

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

BearerAuth

POST /api/v2/modelPackages/fromLeaderboard/

Create model package from a Leaderboard model.

Code samples

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

Body parameter

{
  "computeAllTsIntervals": null,
  "description": "",
  "distributionPredictionModelId": null,
  "modelId": "string",
  "name": null,
  "predictionThreshold": 1
}

Parameters

Name In Type Required Description
body body ModelPackageCreateFromLeaderboard false none

Responses

Status Meaning Description Schema
202 Accepted A job for building model package file was successfully submitted. None
422 Unprocessable Entity Unable to process the Model Package creation request. None

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

BearerAuth

POST /api/v2/modelPackages/fromLearningModel/

Create model package from DataRobot model.

.. minversion:: v2.31 DEPRECATED: please use the following route instead: POST /api/v2/modelPackages/fromLeaderboard/

Code samples

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

Body parameter

{
  "description": "string",
  "distributionPredictionModelId": null,
  "modelId": "string",
  "name": null,
  "predictionThreshold": 1
}

Parameters

Name In Type Required Description
body body ModelPackageCreateFromLearningModel false none

Responses

Status Meaning Description Schema
201 Created none None
403 Forbidden The user does not have permission to create a Model Package. None
404 Not Found Either the model_id not exist or the user does not have permission to view the model and project. None
422 Unprocessable Entity Unable to process the Model Package creation request. None

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

BearerAuth

GET /api/v2/modelPackages/{modelPackageId}/

Retrieve info about a model package.

Code samples

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

Parameters

Name In Type Required Description
modelPackageId path string true ID of the model package.

Example responses

200 Response

{
  "activeDeploymentCount": 0,
  "buildStatus": "inProgress",
  "capabilities": {
    "supportsAutomaticActuals": true,
    "supportsChallengerModels": true,
    "supportsFeatureDriftTracking": true,
    "supportsHumilityRecommendedRules": true,
    "supportsHumilityRules": true,
    "supportsHumilityRulesDefaultCalculations": true,
    "supportsPredictionWarning": true,
    "supportsRetraining": true,
    "supportsScoringCodeDownload": true,
    "supportsSecondaryDatasets": true,
    "supportsSegmentedAnalysisDriftAndAccuracy": true,
    "supportsShapBasedPredictionExplanations": true,
    "supportsTargetDriftTracking": true
  },
  "datasets": {
    "baselineSegmentedBy": [
      "string"
    ],
    "datasetName": "string",
    "holdoutDataCatalogId": "string",
    "holdoutDataCatalogVersionId": "string",
    "holdoutDatasetName": "string",
    "targetHistogramBaseline": "predictions",
    "trainingDataCatalogId": "string",
    "trainingDataCatalogVersionId": "string",
    "trainingDataSize": 0
  },
  "id": "string",
  "importMeta": {
    "containsFearPipeline": true,
    "containsFeaturelists": true,
    "containsLeaderboardMeta": true,
    "containsProjectMeta": true,
    "creatorFullName": "string",
    "creatorId": "string",
    "creatorUsername": "string",
    "dateCreated": "string",
    "originalFileName": "string"
  },
  "isArchived": true,
  "isDeprecated": true,
  "mlpkgFileContents": {
    "allTimeSeriesPredictionIntervals": true
  },
  "modelDescription": {
    "buildEnvironmentType": "DataRobot",
    "description": "string",
    "location": "string",
    "modelCreatedAt": "string",
    "modelCreatorEmail": "string",
    "modelCreatorId": null,
    "modelCreatorName": "string",
    "modelName": "string"
  },
  "modelExecutionType": "dedicated",
  "modelId": "string",
  "modelKind": {
    "isAnomalyDetectionModel": true,
    "isCombinedModel": true,
    "isDecisionFlow": true,
    "isFeatureDiscovery": true,
    "isMultiseries": true,
    "isTimeSeries": true,
    "isUnsupervisedLearning": true
  },
  "name": "string",
  "permissions": [
    "string"
  ],
  "sourceMeta": {
    "decisionFlowId": "string",
    "decisionFlowVersionId": "string",
    "environmentUrl": "http://example.com",
    "fips_140_2Enabled": true,
    "projectCreatedAt": "string",
    "projectCreatorEmail": "string",
    "projectCreatorId": null,
    "projectCreatorName": "string",
    "projectId": "string",
    "projectName": "string",
    "scoringCode": {
      "dataRobotPredictionVersion": "string",
      "location": "local_leaderboard"
    },
    "useCaseDetails": {
      "createdAt": "string",
      "creatorEmail": "string",
      "creatorId": "string",
      "creatorName": "string",
      "id": "string",
      "name": "string"
    }
  },
  "target": {
    "classCount": 0,
    "classNames": [
      "string"
    ],
    "name": "string",
    "predictionProbabilitiesColumn": "string",
    "predictionThreshold": 1,
    "type": "Binary"
  },
  "timeseries": {
    "datetimeColumnFormat": "string",
    "datetimeColumnName": "string",
    "effectiveFeatureDerivationWindowEnd": 0,
    "effectiveFeatureDerivationWindowStart": 0,
    "featureDerivationWindowEnd": 0,
    "featureDerivationWindowStart": 0,
    "forecastDistanceColumnName": "string",
    "forecastDistances": [
      0
    ],
    "forecastDistancesTimeUnit": "MICROSECOND",
    "forecastPointColumnName": "string",
    "isCrossSeries": true,
    "isNewSeriesSupport": true,
    "isTraditionalTimeSeries": true,
    "seriesColumnName": "string"
  },
  "updatedBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "userProvidedId": "string"
}

Responses

Status Meaning Description Schema
200 OK none ModelPackageRetrieveResponse
404 Not Found Either the model package does not exist or the user does not have permission to view the model package. None

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

BearerAuth

POST /api/v2/modelPackages/{modelPackageId}/archive/

(Deprecated in v2.32) Permanently archive a model package. It will no longer be able to be used in new deployments or replacement. It will not be accessible in the model package list api. It will only be accessible at the model package retrieve route for this model package.

Code samples

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/modelPackages/{modelPackageId}/archive/ \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
modelPackageId path string true ID of the model package.

Responses

Status Meaning Description Schema
204 No Content none None

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

BearerAuth

GET /api/v2/modelPackages/{modelPackageId}/capabilities/

Retrieve the capabilities for the model package.

Code samples

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

Parameters

Name In Type Required Description
modelPackageId path string true ID of the model package.

Example responses

200 Response

{
  "data": [
    {
      "messages": [
        "string"
      ],
      "name": "string",
      "supported": true
    }
  ]
}

Responses

Status Meaning Description Schema
200 OK none ModelPackageCapabilitiesRetrieveResponse

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

BearerAuth

GET /api/v2/modelPackages/{modelPackageId}/features/

Retrieve the feature list for given model package.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/modelPackages/{modelPackageId}/features/?offset=0&limit=50 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
offset query integer true The number of features to skip, defaults to 0.
limit query integer true The number of features to return, defaults to 0.
includeNonPredictionFeatures query string false When True will return all raw features in the universe dataset associated with the deployment, and when False will return only those raw features used to make predictions on the deployment.
forSegmentedAnalysis query string false When True, features returned will be filtered to those usable for segmented analysis.
search query string false Case insensitive search against names of the deployment's features.
orderBy query string false Sort order which will be applied to model package feature list. Prefix the attribute name with a dash to sort in descending order, e.g. "-name".
modelPackageId path string true ID of the model package.

Enumerated Values

Parameter Value
includeNonPredictionFeatures [false, False, true, True]
forSegmentedAnalysis [false, False, true, True]
orderBy [name, -name, importance, -importance, featureType, -featureType, dateFormat, -dateFormat, knownInAdvance, -knownInAdvance]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "dateFormat": "string",
      "featureType": "string",
      "importance": 0,
      "knownInAdvance": true,
      "name": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses

Status Meaning Description Schema
200 OK OK. FeatureListResponse

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

BearerAuth

GET /api/v2/modelPackages/{modelPackageId}/sharedRoles/

(Deprecated in v2.32) instead.Get a list of users, groups and organizations who have access to this model package and their roles on the model package.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/modelPackages/{modelPackageId}/sharedRoles/?offset=0&limit=10 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
id query string false Only return roles for a user, group or organization with this identifier.
offset query integer true This many results will be skipped
limit query integer true At most this many results are returned
name query string false Only return roles for a user, group or organization with this name.
shareRecipientType query string false List access controls for recipients with this type.
modelPackageId path string true ID of the model package.

Enumerated Values

Parameter Value
shareRecipientType [user, group, organization]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "id": "string",
      "name": "string",
      "role": "ADMIN",
      "shareRecipientType": "user"
    }
  ],
  "next": "string",
  "previous": "string",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK The model package's access control list. SharingListV2Response
404 Not Found Either the Model Package does not exist or the user does not have permissions to view the Model Package. None
422 Unprocessable Entity Both username and userId were specified None

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

BearerAuth

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

List of bias mitigated models for the selected project.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/biasMitigatedModels/ \
  -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.
parentModelId query string false Retrieve a list of mitigated models for the parent model if specified. Otherwise retrieve a list of all mitigated models for the project.
projectId path string true The project ID

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "biasMitigationTechnique": "preprocessingReweighing",
      "includeBiasMitigationFeatureAsPredictorVariable": true,
      "modelId": "string",
      "parentModelId": "string",
      "protectedFeature": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK Returns Bias Mitigated models results. BiasMitigatedModelsListResponse

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

BearerAuth

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

Add a request to the queue to train a model with bias mitigation applied. If the job has been previously submitted, the request will return 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}/biasMitigatedModels/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}"

Body parameter

{
  "biasMitigationFeature": "string",
  "biasMitigationParentLid": "string",
  "biasMitigationTechnique": "preprocessingReweighing",
  "includeBiasMitigationFeatureAsPredictorVariable": true
}

Parameters

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

Responses

Status Meaning Description Schema
202 Accepted The model training request has been successfully submitted. See Location header. None

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

BearerAuth

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

Get bias mitigation data quality information for a given projectId and featureName.

Code samples

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

Parameters

Name In Type Required Description
featureName query string true Name of feature for mitigation info.
projectId path string true The project ID

Example responses

200 Response

{
  "messages": [
    {
      "additionalInfo": [
        "string"
      ],
      "messageLevel": "CRITICAL",
      "messageText": "string"
    }
  ]
}

Responses

Status Meaning Description Schema
200 OK Dictionary with one entry ("messages") with list of data quality information about a feature. MessagesInfo

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

BearerAuth

POST /api/v2/projects/{projectId}/biasMitigationFeatureInfo/{featureName}/

Submit a job to create bias mitigation data quality information for a given projectId and featureName.

Code samples

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

Parameters

Name In Type Required Description
projectId path string true The project ID
featureName path string true Name of feature for mitigation info.

Responses

Status Meaning Description Schema
202 Accepted A URI of the newly submitted job in the "Location" header. None

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

BearerAuth

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

List all blenders in a project.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/blenderModels/?offset=0&limit=0 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
offset query integer true This many results will be skipped.
limit query integer true At most this many results are returned. If 0, all results.
projectId path string true The project ID

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "blenderMethod": "string",
      "blueprintId": "string",
      "dataSelectionMethod": "duration",
      "featurelistId": "string",
      "featurelistName": "string",
      "hasFinetuners": true,
      "id": "string",
      "isAugmented": true,
      "isFrozen": true,
      "isNClustersDynamicallyDetermined": true,
      "isStarred": true,
      "isTrainedIntoHoldout": true,
      "isTrainedIntoValidation": true,
      "lifecycle": {
        "reason": "string",
        "stage": "active"
      },
      "linkFunction": "string",
      "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
      "modelCategory": "model",
      "modelFamily": "string",
      "modelFamilyFullName": "string",
      "modelIds": [
        "string"
      ],
      "modelNumber": 0,
      "modelType": "string",
      "monotonicDecreasingFeaturelistId": "string",
      "monotonicIncreasingFeaturelistId": "string",
      "nClusters": 0,
      "parentModelId": "string",
      "predictionThreshold": 1,
      "predictionThresholdReadOnly": true,
      "processes": [
        "string"
      ],
      "projectId": "string",
      "samplePct": 0,
      "samplingMethod": "random",
      "supportsComposableMl": true,
      "supportsMonotonicConstraints": true,
      "timeWindowSamplePct": 0,
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses

Status Meaning Description Schema
200 OK A list of all of the blenders in a project. BlenderListResponse
404 Not Found This resource does 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}/blenderModels/

Create a blender from other models using a specified blender method. Note: Time Series projects only allow the following blender methods: "AVG", "MED", "FORECAST_DISTANCE_ENET", and "FORECAST_DISTANCE_AVG".

Code samples

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

Body parameter

{
  "blenderMethod": "PLS",
  "modelIds": [
    "string"
  ]
}

Parameters

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

Responses

Status Meaning Description Schema
202 Accepted Model job successfully added to queue. See the Location header. None
404 Not Found This resource does not exist. None
422 Unprocessable Entity Unable to create a blender or request is not supported in this context. None

Response Headers

Status Header Type Format Description
202 Location string url A url that can be polled to check the status of the job.

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

BearerAuth

POST /api/v2/projects/{projectId}/blenderModels/blendCheck/

Check if models can be blended.

Code samples

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

Body parameter

{
  "blenderMethod": "PLS",
  "modelIds": [
    "string"
  ]
}

Parameters

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

Example responses

200 Response

{
  "blendable": true,
  "reason": "string"
}

Responses

Status Meaning Description Schema
200 OK Information on whether models can be blended and why. BlenderInfoRetrieveResponse
404 Not Found This resource does not exist. None
422 Unprocessable Entity Unable to process request. None

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

BearerAuth

GET /api/v2/projects/{projectId}/blenderModels/{modelId}/

Retrieve a blender. Blenders are a special type of models, so the response includes all attributes that would be in a response to GET /api/v2/projects/{projectId}/models/{modelId}/ as well as some additional ones.

Code samples

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

{
  "blenderMethod": "string",
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelIds": [
    "string"
  ],
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": 0,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Responses

Status Meaning Description Schema
200 OK The blender model. BlenderRetrieveResponse
404 Not Found Specified blender 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}/combinedModels/

Retrieve all existing combined models for this project. .. note::

To retrieve information on the segments for a combined model, retrieve the combined model using [GET /api/v2/projects/{projectId}/combinedModels/{combinedModelId}/][get-apiv2projectsprojectidcombinedmodelscombinedmodelid]

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/combinedModels/ \
  -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": [
    {
      "combinedModelId": "string",
      "isActiveCombinedModel": false,
      "modelCategory": "combined",
      "projectId": "string",
      "segmentationTaskId": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK none CombinedModelListResponse

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

BearerAuth

GET /api/v2/projects/{projectId}/combinedModels/{combinedModelId}/

Retrieve an existing combined model. If available, contains information on which champion model is used for each segment.

Code samples

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

Parameters

Name In Type Required Description
projectId path string true The ID of the project.
combinedModelId path string true The ID of combined model.

Example responses

200 Response

{
  "combinedModelId": "string",
  "isActiveCombinedModel": false,
  "modelCategory": "combined",
  "projectId": "string",
  "segmentationTaskId": "string",
  "segments": [
    {
      "modelId": "string",
      "projectId": "string",
      "segment": "string"
    }
  ]
}

Responses

Status Meaning Description Schema
200 OK none CombinedModelResponse

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

BearerAuth

GET /api/v2/projects/{projectId}/combinedModels/{combinedModelId}/segments/

Retrieve Combined Model segments info (name, related project & model details).

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/combinedModels/{combinedModelId}/segments/ \
  -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.
searchSegmentName query string false Case insensitive search against segment name.
projectId path string true The ID of the project.
combinedModelId path string true The ID of combined model.

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "autopilotDone": true,
      "holdoutUnlocked": true,
      "isFrozen": true,
      "modelAssignedBy": "string",
      "modelAwardTime": "2019-08-24T14:15:22Z",
      "modelCount": 0,
      "modelIcon": [
        0
      ],
      "modelId": "string",
      "modelMetrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
      "modelType": "string",
      "projectId": "string",
      "projectPaused": true,
      "projectStage": "modeling",
      "projectStageDescription": "string",
      "projectStatusError": "string",
      "rowCount": 0,
      "rowPercentage": 0,
      "segment": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK none CombinedModelSegmentsPaginatedResponse

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

BearerAuth

GET /api/v2/projects/{projectId}/combinedModels/{combinedModelId}/segments/download/

Download Combined Model segments info (name, related project & model details) as a CSV.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/combinedModels/{combinedModelId}/segments/download/ \
  -H "Accept: text/csv" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
projectId path string true The ID of the project.
combinedModelId path string true The ID of combined model.

Example responses

200 Response

Responses

Status Meaning Description Schema
200 OK none string

Response Headers

Status Header Type Format Description
200 Content-Disposition string Contains an auto generated filename for this download.

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

BearerAuth

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

List all the models from a datetime partitioned project.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/ \
  -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.
bulkOperationId query string false the ID of the bulk model operation. If specified, only models submitted in scope of this operation will be shown.
projectId path string true The project ID

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "backtests": [
        {
          "index": 0,
          "score": 0,
          "status": "COMPLETED",
          "trainingDuration": "string",
          "trainingEndDate": "2019-08-24T14:15:22Z",
          "trainingRowCount": 0,
          "trainingStartDate": "2019-08-24T14:15:22Z"
        }
      ],
      "blueprintId": "string",
      "dataSelectionMethod": "duration",
      "effectiveFeatureDerivationWindowEnd": 0,
      "effectiveFeatureDerivationWindowStart": 0,
      "featurelistId": "string",
      "featurelistName": "string",
      "forecastWindowEnd": 0,
      "forecastWindowStart": 0,
      "hasFinetuners": true,
      "holdoutScore": 0,
      "holdoutStatus": "COMPLETED",
      "id": "string",
      "isAugmented": true,
      "isFrozen": true,
      "isNClustersDynamicallyDetermined": true,
      "isStarred": true,
      "isTrainedIntoHoldout": true,
      "isTrainedIntoValidation": true,
      "lifecycle": {
        "reason": "string",
        "stage": "active"
      },
      "linkFunction": "string",
      "metrics": "\n        {\n            \"metrics\": {\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"backtesting\": 0.50166,\n                    \"backtestingScores\": [0.51206, 0.49436, null, 0.62516],\n                    \"crossValidation\": null\n                },\n                \"RMSE\": {\n                    \"holdout\": null,\n                    \"validation\": 21.0836,\n                    \"backtesting\": 23.361932,\n                    \"backtestingScores\": [0.4403, 0.4213, null, 0.5132],\n                    \"crossValidation\": null\n                }\n            }\n        }\n",
      "modelCategory": "model",
      "modelFamily": "string",
      "modelFamilyFullName": "string",
      "modelNumber": 0,
      "modelType": "string",
      "monotonicDecreasingFeaturelistId": "string",
      "monotonicIncreasingFeaturelistId": "string",
      "nClusters": 0,
      "parentModelId": "string",
      "predictionThreshold": 1,
      "predictionThresholdReadOnly": true,
      "processes": [
        "string"
      ],
      "projectId": "string",
      "samplePct": null,
      "samplingMethod": "random",
      "supportsComposableMl": true,
      "supportsMonotonicConstraints": true,
      "timeWindowSamplePct": 0,
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingInfo": {
        "holdoutTrainingDuration": "string",
        "holdoutTrainingEndDate": "2019-08-24T14:15:22Z",
        "holdoutTrainingRowCount": 0,
        "holdoutTrainingStartDate": "2019-08-24T14:15:22Z",
        "predictionTrainingDuration": "string",
        "predictionTrainingEndDate": "2019-08-24T14:15:22Z",
        "predictionTrainingRowCount": 0,
        "predictionTrainingStartDate": "2019-08-24T14:15:22Z"
      },
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z",
      "windowsBasisUnit": "MILLISECOND"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses

Status Meaning Description Schema
200 OK The datetime partitioned project's models DatetimeModelsResponse

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

BearerAuth

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

Train a new datetime model.

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 POST https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Body parameter

{
  "blueprintId": "string",
  "featurelistId": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 2,
  "samplingMethod": "random",
  "sourceProjectId": "string",
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingRowCount": 0,
  "useProjectSettings": true
}

Parameters

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

Example responses

202 Response

{
  "message": "string"
}

Responses

Status Meaning Description Schema
202 Accepted The model has been successfully submitted. DatetimeModelSubmissionResponse
422 Unprocessable Entity There was an error submitting the specified job. 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

POST /api/v2/projects/{projectId}/datetimeModels/fromModel/

Retrain an existing datetime model using a new training period for the model training set (with optional time window sampling) or different feature list.

All durations and datetimes should be specified in accordance with the :ref:timestamp and duration formatting rules<time_format>.

Note that only one of trainingDuration or trainingRowCount or trainingStartDate and trainingEndDate should be specified. If trainingStartDate and trainingEndDate are specified, the source model must be frozen.

Code samples

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

Body parameter

{
  "featurelistId": "string",
  "modelId": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 2,
  "samplingMethod": "random",
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z",
  "useProjectSettings": true
}

Parameters

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

Example responses

202 Response

{
  "message": "string"
}

Responses

Status Meaning Description Schema
202 Accepted Retrain an existing datetime model using a new sample size and/or feature list. DatetimeModelSubmissionResponse
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 Model with specified modelId is deprecated, or it doesn't support retraining with specified parameters. 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}/

Look up a particular datetime model All durations and 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}/ \
  -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

{
  "backtests": [
    {
      "index": 0,
      "score": 0,
      "status": "COMPLETED",
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "effectiveFeatureDerivationWindowEnd": 0,
  "effectiveFeatureDerivationWindowStart": 0,
  "featurelistId": "string",
  "featurelistName": "string",
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "hasFinetuners": true,
  "holdoutScore": 0,
  "holdoutStatus": "COMPLETED",
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"backtesting\": 0.50166,\n                    \"backtestingScores\": [0.51206, 0.49436, null, 0.62516],\n                    \"crossValidation\": null\n                },\n                \"RMSE\": {\n                    \"holdout\": null,\n                    \"validation\": 21.0836,\n                    \"backtesting\": 23.361932,\n                    \"backtestingScores\": [0.4403, 0.4213, null, 0.5132],\n                    \"crossValidation\": null\n                }\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": null,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingInfo": {
    "holdoutTrainingDuration": "string",
    "holdoutTrainingEndDate": "2019-08-24T14:15:22Z",
    "holdoutTrainingRowCount": 0,
    "holdoutTrainingStartDate": "2019-08-24T14:15:22Z",
    "predictionTrainingDuration": "string",
    "predictionTrainingEndDate": "2019-08-24T14:15:22Z",
    "predictionTrainingRowCount": 0,
    "predictionTrainingStartDate": "2019-08-24T14:15:22Z"
  },
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z",
  "windowsBasisUnit": "MILLISECOND"
}

Responses

Status Meaning Description Schema
200 OK Datetime model DatetimeModelDetailsResponse

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

BearerAuth

POST /api/v2/projects/{projectId}/datetimeModels/{modelId}/backtests/

Score all the available backtests of a datetime model.

Code samples

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/datetimeModels/{modelId}/backtests/ \
  -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
202 Accepted Scoring of all the available backtests of a datetime model 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

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

Prepare a specific model for deployment. This model will go through the recommendation stages.

Code samples

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

Body parameter

{
  "modelId": "string"
}

Parameters

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

Responses

Status Meaning Description Schema
201 Created Start preparing the model for deployment. None
422 Unprocessable Entity An error occurred when submitting the model job None

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

BearerAuth

GET /api/v2/projects/{projectId}/eureqaDistributionPlot/{solutionId}/

Retrieve Eureqa model details plot.

Available for classification projects only

Code samples

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

Parameters

Name In Type Required Description
projectId path string true The project ID
solutionId path string true The ID of the solution to return data for.

Example responses

200 Response

{
  "bins": [
    {
      "binEnd": 0,
      "binStart": 0,
      "negatives": 0,
      "positives": 0
    }
  ],
  "complexity": 0,
  "error": 0,
  "errorMetric": "string",
  "eureqaSolutionId": "string",
  "expression": "string",
  "expressionAnnotated": "string",
  "threshold": 0
}

Responses

Status Meaning Description Schema
200 OK Eureqa model details plot. EureqaDistributionDetailResponse
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}/eureqaModelDetail/{solutionId}/

Retrieve Eureqa model details plot.

Available for regression projects only

Code samples

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

Parameters

Name In Type Required Description
projectId path string true The project ID
solutionId path string true The ID of the solution to return data for.

Example responses

200 Response

{
  "complexity": 0,
  "error": 0,
  "errorMetric": "string",
  "eureqaSolutionId": "string",
  "expression": "string",
  "expressionAnnotated": "string",
  "plotData": [
    {
      "actual": 0,
      "predicted": 0,
      "row": 0
    }
  ]
}

Responses

Status Meaning Description Schema
200 OK Eureqa model details plot. EureqaModelDetailResponse
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

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

Create a new model from an existing eureqa solution.

Code samples

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

Body parameter

{
  "parentModelId": "string",
  "solutionId": "string"
}

Parameters

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

Responses

Status Meaning Description Schema
200 OK Request accepted, creation is underway. None
404 Not Found Data not found. None
422 Unprocessable Entity Model for this solution already exists. None

Response Headers

Status Header Type Format Description
200 Location string The location at which the new model can be retrieved.

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

BearerAuth

GET /api/v2/projects/{projectId}/eureqaModels/{modelId}/

Retrieve the pareto front for the specified Eureqa model.

Only the best solution in the pareto front will have a corresponding model initially. Models can be created for other solutions using POST /api/v2/projects/{projectId}/eureqaModels/.

Code samples

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

{
  "errorMetric": "string",
  "hyperparameters": {
    "buildingBlocks": {},
    "errorMetric": "string",
    "maxGenerations": 32,
    "numThreads": 0,
    "priorSolutions": [
      "string"
    ],
    "randomSeed": 0,
    "splitMode": "custom",
    "syncMigrations": true,
    "targetExpressionFormat": "None",
    "targetExpressionString": "string",
    "timeoutSec": 0,
    "trainingFraction": 1,
    "trainingSplitExpr": "string",
    "validationFraction": 1,
    "validationSplitExpr": "string",
    "weightExpr": "string"
  },
  "projectId": "string",
  "solutions": [
    {
      "bestModel": true,
      "complexity": 0,
      "error": 0,
      "eureqaSolutionId": "string",
      "expression": "string",
      "expressionAnnotated": "string"
    }
  ],
  "targetType": "Regression"
}

Responses

Status Meaning Description Schema
200 OK Pareto front for the Eureqa model. ParetoFrontResponse
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

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

Train a frozen datetime model. If no training data is specified, the frozen datetime model will be trained on the most recent data using an amount of data that is equivalent to the original model. However, if the equivalent duration does not provide enough rows for training, then the duration will be extended until the minimum is met. Note that this will require the holdout of the project to be unlocked.

All durations and datetimes should be specified in accordance with the :ref:timestamp and duration formatting rules<time_format>.

Note that only one of trainingDuration, trainingRowCount, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.

Code samples

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

Body parameter

{
  "modelId": "string",
  "samplingMethod": "random",
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z",
  "useProjectSettings": true
}

Parameters

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

Example responses

202 Response

{
  "message": "string"
}

Responses

Status Meaning Description Schema
202 Accepted The model has been successfully submitted. DatetimeModelSubmissionResponse
403 Forbidden User does not have permissions to manage models. None
404 Not Found Model with specified modelId does not exist, or user does not have access to the project. None
422 Unprocessable Entity Model with specified modelId is deprecated, or it does not support retraining with specified parameters. 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}/frozenModels/

List all frozen models from a project.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/frozenModels/?offset=0&limit=0 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
offset query integer true This many results will be skipped.
limit query integer true At most this many results are returned. If 0, all results.
withMetric query string false If specified, the returned models will only have scores for this metric. If not, all metrics will be included.
projectId path string true The project ID

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "blueprintId": "string",
      "dataSelectionMethod": "duration",
      "featurelistId": "string",
      "featurelistName": "string",
      "hasFinetuners": true,
      "id": "string",
      "isAugmented": true,
      "isFrozen": true,
      "isNClustersDynamicallyDetermined": true,
      "isStarred": true,
      "isTrainedIntoHoldout": true,
      "isTrainedIntoValidation": true,
      "lifecycle": {
        "reason": "string",
        "stage": "active"
      },
      "linkFunction": "string",
      "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
      "modelCategory": "model",
      "modelFamily": "string",
      "modelFamilyFullName": "string",
      "modelNumber": 0,
      "modelType": "string",
      "monotonicDecreasingFeaturelistId": "string",
      "monotonicIncreasingFeaturelistId": "string",
      "nClusters": 0,
      "parentModelId": "string",
      "predictionThreshold": 1,
      "predictionThresholdReadOnly": true,
      "processes": [
        "string"
      ],
      "projectId": "string",
      "samplePct": 0,
      "samplingMethod": "random",
      "supportsComposableMl": true,
      "supportsMonotonicConstraints": true,
      "timeWindowSamplePct": 0,
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "next": "string",
  "previous": "string",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK A list of frozen models in the project. FrozenModelListResponse
404 Not Found This resource does 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}/frozenModels/

Train a new frozen model with parameters from an existing model. Frozen models use tuning parameters from another model on the leaderboard, allowing them to be retrained on a larger amount of the training data more efficiently. To specify the amount of data to use to train the model, use either samplePct to express a percentage of the rows of the dataset to use or trainingRowCount to express the number of rows to use. If neither samplePct or trainingRowCount is specified, the model will be trained on the maximum available training data that can be used to train an in-memory model. For projects using smart sampling, samplePct and trainingRowCount will be interpreted as a percent or number of rows of the minority class. When configuring retraining sample sizes for models in projects with large row counts, DataRobot recommends requesting sample sizes using integer row counts instead of percentages. This is because percentages map to many actual possible row counts and only one of which is the actual sample size for up to validation. For example, if a project has 199,408 rows and you request a 64% sample size, any number of rows between 126,625 rows and 128,618 rows maps to 64% of the data. Using actual integer row counts (or project.max_training_rows) avoids ambiguity around how many rows of data you want the model to use.

Code samples

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

Body parameter

{
  "modelId": "string",
  "nClusters": 2,
  "samplePct": 0,
  "trainingRowCount": 0
}

Parameters

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

Responses

Status Meaning Description Schema
204 No Content The frozen model has been successfully submitted. None
404 Not Found This resource does not exist. None
422 Unprocessable Entity Unable to process request. None

Response Headers

Status Header Type Format Description
204 Location string url Contains a url at which the job processing the model can be retrieved as with GET /api/v2/projects/{projectId}/modelJobs/{jobId}/..

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

BearerAuth

GET /api/v2/projects/{projectId}/frozenModels/{modelId}/

Look up a particular frozen model. If model with given ID exists but it's not frozen, returns 404 Not Found.

Code samples

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

{
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": 0,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Responses

Status Meaning Description Schema
200 OK The frozen model. ModelDetailsResponse
404 Not Found No such frozen model found. None

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

BearerAuth

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

List modeling jobs.

Code samples

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

Parameters

Name In Type Required Description
status query string false If provided, only jobs with the same status will be included in the results; otherwise, queued and inprogress jobs (but not errored jobs) will be returned.
projectId path string true The project ID.

Enumerated Values

Parameter Value
status [queue, inprogress, error]

Example responses

200 Response

[
  {
    "data": [
      {
        "blueprintId": "string",
        "featurelistId": "string",
        "id": "string",
        "isBlocked": true,
        "isTrainedOnGpu": true,
        "modelCategory": "model",
        "modelId": "string",
        "modelType": "string",
        "processes": [
          "string"
        ],
        "projectId": "string",
        "samplePct": 0,
        "status": "queue"
      }
    ]
  }
]

Responses

Status Meaning Description Schema
200 OK List of modeling jobs. Inline

Response Schema

Status Code 200

Name Type Required Restrictions Description
anonymous [ModelingJobListResponse] false none
» data [ModelJobResponse] true List of modeling jobs.
»» blueprintId string true The blueprint used by the model - note that this is not an ObjectId.
»» featurelistId string true The ID of the featurelist the model is using.
»» id string true The job ID.
»» isBlocked boolean true True if a job is waiting for its dependencies to be resolved first.
»» isTrainedOnGpu boolean false True if the job was trained using GPU capabilities
»» modelCategory string true Indicates what kind of model this is. Will be combined for combined models.
»» modelId string true The ID of the model
»» modelType string true The type of model used by the job.
»» processes [string] true List of processes the modeling job includes
»» projectId string true The project the job belongs to.
»» samplePct number false The percentage of the dataset the job is using.
»» status string true The status of the job.

Enumerated Values

Property Value
modelCategory [model, prime, blend]
status [queue, inprogress, error, ABORTED, COMPLETED]

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

BearerAuth

DELETE /api/v2/projects/{projectId}/modelJobs/{jobId}/

Cancel a modeling job

Code samples

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

Parameters

Name In Type Required Description
projectId path string true The project ID.
jobId path string true The job ID

Responses

Status Meaning Description Schema
204 No Content The job has been successfully cancelled. None
404 Not Found no job with jobId found, or the job has already completed None

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

BearerAuth

GET /api/v2/projects/{projectId}/modelJobs/{jobId}/

Look up a particular modeling job

Code samples

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

Parameters

Name In Type Required Description
projectId path string true The project ID.
jobId path string true The job ID

Example responses

200 Response

{
  "blueprintId": "string",
  "featurelistId": "string",
  "id": "string",
  "isBlocked": true,
  "isTrainedOnGpu": true,
  "modelCategory": "model",
  "modelId": "string",
  "modelType": "string",
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": 0,
  "status": "queue"
}

Responses

Status Meaning Description Schema
200 OK A modeling job ModelJobResponse
303 See Other Task is completed, see Location header for the location of a new resource None

Response Headers

Status Header Type Format Description
200 Location string url if a status code 303 was returned, will contain a url at which the completed model can be retrieved`

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

BearerAuth

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

Lists all the models from a project.

Code samples

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

Parameters

Name In Type Required Description
withMetric query string false If specified, the returned models will only have scores for this metric. If not, all metrics will be included.
showInSampleScores query boolean false If specified, will return metric scores for models trained into validation/holdout for projects that do not have stacked predictions.
name query string false If specified, filters for models with a model type matching name.
samplePct query number false If specified, filters for models with a matching sample percentage.
isStarred query string false If specified, filters for models marked as starred.
orderBy query string false A comma-separated list of metrics to sort by. If metric is prefixed with a '-', models are sorted by this metric in descending order, otherwise are sorted in ascending order. Valid sorting metrics are metric and samplePct. Use of metric sorts models by metric value selected for this project using the validation score. Use of the prefix accounts for the direction of the metric, so -metric will sort in order of decreasing 'goodness', which may be opposite to the natural numerical order. If not specified, -metric will be used.
projectId path string true The project ID.

Enumerated Values

Parameter Value
isStarred [false, False, true, True]
orderBy [metric, -metric, samplePct, -samplePct]

Example responses

200 Response

[
  {
    "blueprintId": "string",
    "dataSelectionMethod": "duration",
    "featurelistId": "string",
    "featurelistName": "string",
    "hasFinetuners": true,
    "id": "string",
    "isAugmented": true,
    "isFrozen": true,
    "isNClustersDynamicallyDetermined": true,
    "isStarred": true,
    "isTrainedIntoHoldout": true,
    "isTrainedIntoValidation": true,
    "lifecycle": {
      "reason": "string",
      "stage": "active"
    },
    "linkFunction": "string",
    "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
    "modelCategory": "model",
    "modelFamily": "string",
    "modelFamilyFullName": "string",
    "modelNumber": 0,
    "modelType": "string",
    "monotonicDecreasingFeaturelistId": "string",
    "monotonicIncreasingFeaturelistId": "string",
    "nClusters": 0,
    "parentModelId": "string",
    "predictionThreshold": 1,
    "predictionThresholdReadOnly": true,
    "processes": [
      "string"
    ],
    "projectId": "string",
    "samplePct": 0,
    "samplingMethod": "random",
    "supportsComposableMl": true,
    "supportsMonotonicConstraints": true,
    "timeWindowSamplePct": 0,
    "trainingDuration": "string",
    "trainingEndDate": "2019-08-24T14:15:22Z",
    "trainingRowCount": 0,
    "trainingStartDate": "2019-08-24T14:15:22Z"
  }
]

Responses

Status Meaning Description Schema
200 OK The project's models Inline

Response Schema

Status Code 200

Name Type Required Restrictions Description
anonymous [ModelDetailsResponse] false none
» blueprintId string true The blueprint used to construct the model.
» dataSelectionMethod string false Identifies which setting defines the training size of the model when making predictions and scoring. Only used by datetime models.
» featurelistId string¦null true the ID of the featurelist used by the model
» featurelistName string¦null true the name of the featurelist used by the model.If null, the model was trained on multiple feature lists.
» hasFinetuners boolean false Whether a model has fine tuners.
» id string true the ID of the model
» isAugmented boolean false Whether a model was trained using augmentation.
» isFrozen boolean true Indicates whether the model is frozen, i.e., uses tuning parameters from a parent model.
» isNClustersDynamicallyDetermined boolean false Whether number of clusters is dynamically determined. Only valid in unsupervised clustering projects.
» isStarred boolean true whether the model has been starred
» isTrainedIntoHoldout boolean true Indicates if model used holdout data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or whenthe model's training row count was greater than the max allowed validation size.
» isTrainedIntoValidation boolean true Indicates if model used validation data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or when the model's training row count was greater than the max allowed training size.
» lifecycle ModelLifecycle true none
»» reason string¦null true Reason for lifecycle stage. None if model is active.
»» stage string true Model lifecycle stage.
» linkFunction string¦null true The link function the final modeler uses in the blueprint. If no link function exists, returns null.
» metrics object true the performance of the model according to various metrics, where each metric has validation, crossValidation, holdout, and training scores reported, or null if they have not been computed.
» modelCategory string true Indicates the kind of model. Returns prime for DataRobot Prime models, blend for blender models, combined for combined models, and model for all other models.
» modelFamily string true the family model belongs to, e.g. SVM, GBM, etc.
» modelFamilyFullName string true The full name of the family that the model belongs to. For e.g., Support Vector Machine, Gradient Boosting Machine, etc.
» modelNumber integer¦null true minimum: 0 (exclusive)
The model number from the leaderboard.
» modelType string true identifies the model, e.g. Nystroem Kernel SVM Regressor
» monotonicDecreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
» monotonicIncreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
» nClusters integer¦null false The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
» parentModelId string¦null true The ID of the parent model if the model is frozen or a result of incremental learning. Null otherwise.
» predictionThreshold number true maximum: 1
minimum: 0
threshold used for binary classification in predictions.
» predictionThresholdReadOnly boolean true indicates whether modification of a predictions threshold is forbidden. Since v2.22 threshold modification is allowed.
» processes [string]¦null true list of processes used by the model
» projectId string true the ID of the project to which the model belongs
» samplePct number¦null true minimum: 0 (exclusive)
the percentage of the dataset used in training the model
» samplingMethod string false indicates sampling method used to select training data in datetime models. For row-based project this is the way how requested number of rows are selected.For other projects (duration-based, start/end, project settings) - how specified percent of rows (timeWindowSamplePct) is selected from specified time window.
» supportsComposableMl boolean true indicates whether this model is supported in Composable ML.
» supportsMonotonicConstraints boolean true whether this model supports enforcing monotonic constraints
» timeWindowSamplePct integer¦null false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99, indicating the percentage of sampling within the time window. The points kept are determined by samplingMethod option. Will be null if no sampling was specified. Only used by datetime models.
» trainingDuration string¦null true the duration spanned by the dates in the partition column for the data used to train the model
» trainingEndDate string(date-time)¦null true the end date of the dates in the partition column for the data used to train the model
» trainingRowCount integer¦null true minimum: 0 (exclusive)
The number of rows used to train the model.
» trainingStartDate string(date-time)¦null true the start date of the dates in the partition column for the data used to train the model

Enumerated Values

Property Value
dataSelectionMethod [duration, rowCount, selectedDateRange, useProjectSettings]
stage [active, deprecated, disabled]
modelCategory [model, prime, blend, combined, incrementalLearning]
samplingMethod [random, latest]

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

BearerAuth

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

Train a new model. To specify the amount of data to use to train the model, use either samplePct to express a percentage of the rows of the dataset to use or trainingRowCount to express the number of rows to use. If neither samplePct or trainingRowCount is specified, the model will be trained on the maximum available training data that can be used to train an in-memory model. For projects using smart sampling, samplePct and trainingRowCount will be interpreted as a percent or number of rows of the minority class. When configuring retraining sample sizes for models in projects with large row counts, DataRobot recommends requesting sample sizes using integer row counts instead of percentages. This is because percentages map to many actual possible row counts and only one of which is the actual sample size for up to validation. For example, if a project has 199,408 rows and you request a 64% sample size, any number of rows between 126,625 rows and 128,618 rows maps to 64% of the data. Using actual integer row counts (or project.max_training_rows) avoids ambiguity around how many rows of data you want the model to use.

Code samples

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

Body parameter

{
  "blueprintId": "string",
  "featurelistId": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 2,
  "samplePct": 0,
  "scoringType": "validation",
  "sourceProjectId": "string",
  "trainingRowCount": 0
}

Parameters

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

Responses

Status Meaning Description Schema
202 Accepted Creation has successfully started. See the Location header. None
422 Unprocessable Entity Could not create new job 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

POST /api/v2/projects/{projectId}/models/fromModel/

Retrain an existing model using a new sample size and/or feature list.When configuring retraining sample sizes for models in projects with large row counts, DataRobot recommends requesting sample sizes using integer row counts instead of percentages. This is because percentages map to many actual possible row counts and only one of which is the actual sample size for up to validation. For example, if a project has 199,408 rows and you request a 64% sample size, any number of rows between 126,625 rows and 128,618 rows maps to 64% of the data. Using actual integer row counts (or project.max_training_rows) avoids ambiguity around how many rows of data you want the model to use. Note that only one of samplePct or trainingRowCount should be specified.

Code samples

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

Body parameter

{
  "featurelistId": "string",
  "modelId": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 2,
  "samplePct": 0,
  "scoringType": "validation",
  "trainingRowCount": 0
}

Parameters

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

Example responses

202 Response

{
  "message": "string"
}

Responses

Status Meaning Description Schema
202 Accepted Retrain an existing model using a new sample size and/or feature list. ModelRetrainResponse
422 Unprocessable Entity model with specified modelId is deprecated, or it doesn't support retraining using a new sample size and/or feature list 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

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

Delete a model from the leaderboard

Code samples

# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/ \
  -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 model has been successfully deleted. None
404 Not Found This resource does not exist. None
422 Unprocessable Entity Unable to process the request. 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}/

Look up a particular model.

Code samples

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

{
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": 0,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Responses

Status Meaning Description Schema
200 OK The model ModelDetailsResponse

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

BearerAuth

PATCH /api/v2/projects/{projectId}/models/{modelId}/

Updates a model's attribute(s)

Code samples

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

Body parameter

{
  "isStarred": true,
  "predictionThreshold": 1
}

Parameters

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

Responses

Status Meaning Description Schema
204 No Content The model has been successfully updated with new attributes. None
404 Not Found This resource does not exist. None
422 Unprocessable Entity Unable to process the request. 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}/advancedTuning/

Submit a job to make a new version of the model with different advanced tuning parameters. Note: This route currently supports all models other than: OSS, blenders, prime, scaleout, baseline and user-created. Currently, only single-stage models (most simple models) are supported. Blueprints that run multiple steps, for example one step to predict zero vs nonzero and a second step to determine the value of nonzero predictions, are not supported. (:ref:Advanced Tuning documentation <grid_search>). Parameters may be omitted from this endpoint. If a parameter is omitted, its currentValue will be used. To see the possible parameter IDs and constraints on possible values, see GET /api/v2/projects/{projectId}/models/{modelId}/advancedTuning/parameters/.

Code samples

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

Body parameter

{
  "tuningDescription": "string",
  "tuningParameters": [
    {
      "parameterId": "string",
      "value": "string"
    }
  ]
}

Parameters

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

Responses

Status Meaning Description Schema
202 Accepted The job has been successfully submitted. See the Location header. None
403 Forbidden Permission denied creating advanced tuned model None
404 Not Found This resource does not exist. None
413 Payload Too Large Tuning request is too large None
422 Unprocessable Entity Could not create new job. None

Response Headers

Status Header Type Format Description
202 Location string url A url at which the job processing the model can be retrieved.

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

BearerAuth

GET /api/v2/projects/{projectId}/models/{modelId}/advancedTuning/parameters/

Retrieve information about all advanced tuning parameters available for the specified model. Note: This route currently supports all models other than: OSS, blenders, prime, scaleout, baseline and user-created

Code samples

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

{
  "tuningDescription": "string",
  "tuningParameters": [
    {
      "constraints": {
        "ascii": {
          "supportsGridSearch": true
        },
        "float": {
          "max": 0,
          "min": 0,
          "supportsGridSearch": true
        },
        "floatList": {
          "maxLength": 0,
          "maxVal": 0,
          "minLength": 0,
          "minVal": 0,
          "supportsGridSearch": true
        },
        "int": {
          "max": 0,
          "min": 0,
          "supportsGridSearch": true
        },
        "intList": {
          "maxLength": 0,
          "maxVal": 0,
          "minLength": 0,
          "minVal": 0,
          "supportsGridSearch": true
        },
        "select": {
          "supportsGridSearch": true,
          "values": [
            "string"
          ]
        },
        "selectgrid": {
          "supportsGridSearch": true,
          "values": [
            "string"
          ]
        },
        "unicode": {
          "supportsGridSearch": true
        }
      },
      "currentValue": "string",
      "defaultValue": "string",
      "parameterId": "string",
      "parameterName": "string",
      "taskName": "string",
      "vertexId": "string"
    }
  ]
}

Responses

Status Meaning Description Schema
200 OK The information about all advanced tuning parameters available for the specified model. AdvancedTuningArgumentsRetrieveResponse
403 Forbidden Permission denied creating advanced tuned model. None
404 Not Found This resource does not exist. None
422 Unprocessable Entity This model does not support advanced tuning. 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}/clusterNames/

Retrieve all cluster names assigned to an unsupervised cluster model

Code samples

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

{
  "clusters": [
    {
      "name": "string",
      "percent": 100
    },
    {
      "name": "string",
      "percent": 100
    }
  ],
  "modelId": "string",
  "projectId": "string"
}

Responses

Status Meaning Description Schema
200 OK Retrieve all cluster names for the model ClusterNamesResponse
404 Not Found Could not find unsupervised clustering model. Possible reasons include: 1. Provided model id points to a model that does not exist in specified project. 2. Provided model has incompatible type. Method requires model to be unsupervised clustering model. None

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

BearerAuth

PATCH /api/v2/projects/{projectId}/models/{modelId}/clusterNames/

Update and then retrieve all cluster names assigned to an unsupervised cluster model

Code samples

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

Body parameter

{
  "clusterNameMappings": [
    {
      "currentName": "string",
      "newName": "string"
    }
  ]
}

Parameters

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

Example responses

200 Response

{
  "clusters": [
    {
      "name": "string",
      "percent": 100
    },
    {
      "name": "string",
      "percent": 100
    }
  ],
  "modelId": "string",
  "projectId": "string"
}

Responses

Status Meaning Description Schema
200 OK Update cluster names and then retrieve all cluster names for the model ClusterNamesResponse
404 Not Found Could not find unsupervised clustering model. Possible reasons include: 1. Provided model id points to a model which does not exists in specified project. 2. Provided model has incompatible type. Method requires model to be unsupervised clustering model. None
422 Unprocessable Entity The request cannot be processed. Possible reasons include: 1. Mapping contains invalid current cluster name and referenced cluster was not found. 2. Mapping is invalid as after update, clusters will not be uniquely identifiable by name. 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}/crossValidation/

Run Cross Validation on a model.

Code samples

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/crossValidation/ \
  -H "Content-Type: 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

Responses

Status Meaning Description Schema
202 Accepted The model has been successfully submitted. None
422 Unprocessable Entity Unable to process the request. None

Response Headers

Status Header Type Format Description
202 Location string url Contains a url at which the job processing the model can be retrieved

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

BearerAuth

GET /api/v2/projects/{projectId}/models/{modelId}/crossValidationScores/

    Get Cross Validation scores for each partition in a model.
    .. note:: Individual partition scores are only available for newer models; older models that
              have cross validation score calculated will need to be retrained.

Code samples

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

Parameters

Name In Type Required Description
metric query string false Set to the name of a metric to only return results for that metric.
partition query number false Set to a value such as 1.0, 2.0 to only return results for the specified partition.
projectId path string true The project ID
modelId path string true The model ID

Example responses

200 Response

{
  "cvScores": "\n        {\n            \"cvScores\": {\n                \"FVE Gamma\": {\n                    \"0.0\": 0.24334,\n                    \"1.0\": 0.17757,\n                    \"2.0\": 0.21803,\n                    \"3.0\": 0.20185,\n                    \"4.0\": 0.20576\n                },\n                \"FVE Poisson\": {\n                    \"0.0\": 0.24527,\n                    \"1.0\": 0.22092,\n                    \"2.0\": 0.22451,\n                    \"3.0\": 0.24417,\n                    \"4.0\": 0.21654\n                }\n            }\n        }\n"
}

Responses

Status Meaning Description Schema
200 OK The Cross Validation scores for each partition in a model. CrossValidationRetrieveResponse
404 Not Found 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}/models/{modelId}/features/

List the features used in a model

Code samples

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

{
  "aPrioriFeatureNames": [
    "string"
  ],
  "featureNames": [
    "string"
  ],
  "knownInAdvanceFeatureNames": [
    "string"
  ]
}

Responses

Status Meaning Description Schema
200 OK The features used in a model. ModelFeatureListResponse
404 Not Found This resource does not exist. 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}/missingReport/

Retrieve a summary of how the model's subtasks handle missing values Only models built after the missing value report feature was added will have reports, and only models with at least one imputation or encoding task, e.g. ordinal encoding, missing value imputation. Blenders and scaleout models do not support Missing Value reports.

    The report will describe how each feature's missing values were treated, and report how many
    missing values were present in the training data. Features which were not processed by a
    given blueprint task will not mention it: for instance, a categorical feature with many
    unique values may not be considered eligible for processing by a One-Hot Encoding

    Report is collected for those features which are considered eligible by given
    blueprint task. For instance, categorical feature with a lot of unique values may not be
    considered as eligible in One-Hot Encoding Task.

Code samples

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

{
  "missingValuesReport": [
    {
      "feature": "string",
      "missingCount": 0,
      "missingPercentage": 1,
      "tasks": {
        "property1": {
          "descriptions": [
            "string"
          ],
          "name": "string"
        },
        "property2": {
          "descriptions": [
            "string"
          ],
          "name": "string"
        }
      },
      "type": "string"
    }
  ]
}

Responses

Status Meaning Description Schema
200 OK Retrieve a summary of how the model's subtasks handle missing values. MissingReportRetrieve
404 Not Found Could not found missing value report for provided project & model id. 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}/numIterationsTrained/

Retrieve the actual number of iterations or estimators trained by a tree-based early stopping model.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/numIterationsTrained/ \
  -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": [
    {
      "numIterations": 0,
      "stage": "string"
    }
  ],
  "modelId": "string",
  "projectId": "string"
}

Responses

Status Meaning Description Schema
200 OK The number of estimators/iterations trained NumIterationsTrainedResponse
404 Not Found Cannot retrieve early stopping information for this 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}/parameters/

Retrieve model parameters. These are the parameters that appear in the webapp on the Coefficients tab. Note that they are only available for some models.

Code samples

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

{
  "derivedFeatures": [
    {
      "coefficient": 0,
      "derivedFeature": "string",
      "originalFeature": "string",
      "stageCoefficients": [
        {
          "coefficient": 0,
          "stage": "string"
        }
      ],
      "transformations": [
        {
          "name": "string",
          "value": "string"
        }
      ],
      "type": "string"
    }
  ],
  "parameters": [
    {
      "name": "string",
      "value": "string"
    }
  ]
}

Responses

Status Meaning Description Schema
200 OK The parameters of the model. ModelParametersRetrieveResponse
422 Unprocessable Entity Unable to process the request. 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}/predictionIntervals/

Retrieve prediction intervals (in descending order) that are already calculated for this model. Note that the project this model belongs to must be a time series project.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/models/{modelId}/predictionIntervals/ \
  -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.
projectId path string true The project to retrieve prediction intervals for. Must be a time series project.
modelId path string true The model to retrieve prediction intervals for.

Example responses

200 Response

{
  "count": 0,
  "data": [
    0
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK Request was successful. PredictionIntervalsListResponse

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

BearerAuth

POST /api/v2/projects/{projectId}/models/{modelId}/predictionIntervals/

Submit a job to calculate prediction intervals for the specified percentiles for this model. Note that the project this model belongs to must be a time series project.

Code samples

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

Body parameter

{
  "percentiles": [
    0
  ]
}

Parameters

Name In Type Required Description
projectId path string true The project to calculate prediction intervals for. Must be a time series project.
modelId path string true The model to calculate prediction intervals for.
body body PredictionIntervalsCreate false none

Example responses

202 Response

{
  "message": "string"
}

Responses

Status Meaning Description Schema
202 Accepted Job was successfully submitted. See Location header. PredictionIntervalsCreateResponse

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}/primeInfo/

Check if a model can be approximated by DataRobot Prime

Code samples

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

Parameters

Name In Type Required Description
projectId path string true the project the model belongs to
modelId path string true the model to check

Example responses

200 Response

{
  "canMakePrime": true,
  "message": "string",
  "messageId": 0
}

Responses

Status Meaning Description Schema
200 OK none PrimeInfoRetrieveResponse

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

BearerAuth

GET /api/v2/projects/{projectId}/models/{modelId}/primeRulesets/

List all the rulesets approximating a model

When rulesets are created for the parent model, all of the rulesets are created at once, but not all rulesets have corresponding Prime models (until they are directly requested).

Code samples

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

Parameters

Name In Type Required Description
projectId path string true the project the model belongs to
modelId path string true the model to find approximating rulesets for

Example responses

200 Response

[
  {
    "modelId": "string",
    "parentModelId": "string",
    "projectId": "string",
    "ruleCount": 0,
    "rulesetId": 0,
    "score": 0
  }
]

Responses

Status Meaning Description Schema
200 OK none Inline

Response Schema

Status Code 200

Name Type Required Restrictions Description
anonymous [PrimeRulesetsListResponse] false none
» modelId string true the ID of the Prime model using this ruleset (if it exists) or null
» parentModelId string true ID of the model this ruleset approximates
» projectId string true the project this ruleset belongs to
» ruleCount integer true the number of rules used by this ruleset
» rulesetId integer true the ID of the ruleset
» score number true the validation score of the ruleset

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

BearerAuth

POST /api/v2/projects/{projectId}/models/{modelId}/primeRulesets/

Approximate an existing model on the leaderboard with DataRobot Prime. A request body should be an empty JSON {}

Code samples

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

Body parameter

{}

Parameters

Name In Type Required Description
projectId path string true the project the model to approximate belongs to
modelId path string true the model to approximate
body body PrimeRulesetsCreatePayload false none

Responses

Status Meaning Description Schema
202 Accepted The request was understood and accepted, and is now being worked on. See the Location header None

Response Headers

Status Header Type Format Description
202 Location string url a url that can be polled to check the status of the job

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

BearerAuth

GET /api/v2/projects/{projectId}/models/{modelId}/scoringCode/

Retrieve Scoring Code for making new predictions from an existing model offline. You need the "Scoring Code" feature enabled to use this route.

By default, returns a compiled executable JAR that can be executed locally to calculate model predictions, or it can be used as a library for a Java application. Execute it with the '--help` parameters to learn how to use it as a command-line utility. See model API documentation (https://javadoc.io/doc/com.datarobot/datarobot-prediction/latest/index.html) to be able to use it inside an existing Java application.

With the sourceCode query parameter set to 'true', returns a source code archive that can be used to review internal calculations of the model. This JAR is NOT executable.

See "https://docs.datarobot.com/en/docs/predictions/port-pred/scoring-code/index.html" in DataRobot application for more information.

Code samples

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

Parameters

Name In Type Required Description
sourceCode query string false If set to "true", the downloaded JAR file will contain only the source code and will not be executable.
projectId path string true the project that created the model
modelId path string true the model to use

Enumerated Values

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

Responses

Status Meaning Description Schema
200 OK JAR file None

Response Headers

Status Header Type Format Description
200 Content-Disposition string attachment; filename="<"filename">".jar The suggested filename for the scoring code is dynamically generated
200 Content-Type string application/java-archive

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

BearerAuth

GET /api/v2/projects/{projectId}/models/{modelId}/supportedCapabilities/

Get supported capabilities for a model.

Code samples

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

{
  "eligibleForPrime": true,
  "hasParameters": true,
  "hasWordCloud": true,
  "reasons": {
    "supportsDocumentTextExtractionSampleInsight": "string",
    "supportsImageActivationMaps": "string",
    "supportsImageEmbedding": "string",
    "supportsLiftChart": "string",
    "supportsResiduals": "string",
    "supportsRocCurve": "string"
  },
  "supportsBlending": true,
  "supportsCodeGeneration": true,
  "supportsCoefficients": true,
  "supportsDocumentTextExtractionSampleInsight": true,
  "supportsEarlyStopping": true,
  "supportsImageActivationMaps": true,
  "supportsImageEmbedding": true,
  "supportsLiftChart": true,
  "supportsModelPackageExport": true,
  "supportsModelTrainingMetrics": true,
  "supportsMonotonicConstraints": true,
  "supportsNNVisualizations": true,
  "supportsResiduals": true,
  "supportsRocCurve": true,
  "supportsShap": true
}

Responses

Status Meaning Description Schema
200 OK Successfully returned model capability information. ModelCapabilitiesRetrieveResponse
404 Not Found Resource 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}/primeFiles/

List all DataRobot Prime files available for download

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/primeFiles/ \
  -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. To specify no limit, use 0. The default may change and a maximum limit may be imposed without notice.
parentModelId query string false if specified only Prime files approximating the specified parent model will be returned; otherwise all applicable Prime files will be returned.
modelId query string false if specified only Prime files with code used in the specified prime model will be returned; otherwise all applicable Prime files will be returned
projectId path string true the project to list available files for

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "id": "string",
      "isValid": true,
      "language": "Python",
      "modelId": "string",
      "parentModelId": "string",
      "projectId": "string",
      "rulesetId": 0
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses

Status Meaning Description Schema
200 OK none PrimeFileListResponse

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

BearerAuth

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

Request creation and validation of source code from a Prime model

Code samples

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

Body parameter

{
  "language": "Python",
  "modelId": "string"
}

Parameters

Name In Type Required Description
projectId path string true the project the Prime model belongs to
body body PrimeFileCreate false none

Responses

Status Meaning Description Schema
202 Accepted prime validation job added to queue. See the Location header. None

Response Headers

Status Header Type Format Description
202 Location string url a url that can be polled to check the status of prime validation job

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

BearerAuth

GET /api/v2/projects/{projectId}/primeFiles/{primeFileId}/

Retrieve metadata about a DataRobot Prime file available for download

Code samples

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

Parameters

Name In Type Required Description
projectId path string true the project the file belongs to
primeFileId path string true the file to retrieve

Example responses

200 Response

{
  "id": "string",
  "isValid": true,
  "language": "Python",
  "modelId": "string",
  "parentModelId": "string",
  "projectId": "string",
  "rulesetId": 0
}

Responses

Status Meaning Description Schema
200 OK none PrimeFileResponse

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

BearerAuth

GET /api/v2/projects/{projectId}/primeFiles/{primeFileId}/download/

Download code from an existing Prime file

Code samples

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

Parameters

Name In Type Required Description
projectId path string true the project the file belongs to
primeFileId path string true the Prime file to download code from

Responses

Status Meaning Description Schema
200 OK The response will contain a file with the executable code from the Prime file None

Response Headers

Status Header Type Format Description
200 Content-Disposition string Will be attachment;filename="<"filename">". The suggested filename will depend on the language Prime file was generated for.

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

BearerAuth

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

List all Prime models in a project

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/primeModels/ \
  -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 to list models from

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "blueprintId": "string",
      "dataSelectionMethod": "duration",
      "featurelistId": "string",
      "featurelistName": "string",
      "hasFinetuners": true,
      "id": "string",
      "isAugmented": true,
      "isFrozen": true,
      "isNClustersDynamicallyDetermined": true,
      "isStarred": true,
      "isTrainedIntoHoldout": true,
      "isTrainedIntoValidation": true,
      "lifecycle": {
        "reason": "string",
        "stage": "active"
      },
      "linkFunction": "string",
      "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
      "modelCategory": "model",
      "modelFamily": "string",
      "modelFamilyFullName": "string",
      "modelNumber": 0,
      "modelType": "string",
      "monotonicDecreasingFeaturelistId": "string",
      "monotonicIncreasingFeaturelistId": "string",
      "nClusters": 0,
      "parentModelId": "string",
      "predictionThreshold": 1,
      "predictionThresholdReadOnly": true,
      "processes": [
        "string"
      ],
      "projectId": "string",
      "ruleCount": 0,
      "rulesetId": 0,
      "samplePct": 0,
      "samplingMethod": "random",
      "score": 0,
      "supportsComposableMl": true,
      "supportsMonotonicConstraints": true,
      "timeWindowSamplePct": 0,
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses

Status Meaning Description Schema
200 OK none PrimeModelListResponse

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

BearerAuth

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

Create a Prime model using a particular ruleset.

DataRobot Prime is not available for multiclass projects.

Once rulesets approximating a parent model have been created, using POST /api/v2/projects/(projectId)/models/(modelId)/primeRulesets/, this route will allow creation of a Prime model using one of those rulesets.

Available rulesets can be retrieved via GET /api/v2/projects/(projectId)/models/(modelId)/primeRulesets/.

Code samples

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

Body parameter

{
  "parentModelId": "string",
  "rulesetId": 0
}

Parameters

Name In Type Required Description
projectId path string true the project in which to create the model
body body PrimeModelCreatePayload false none

Responses

Status Meaning Description Schema
202 Accepted Prime model creation job successfully added to queue. See the Location header. None

Response Headers

Status Header Type Format Description
202 Location string url a url that can be polled to check the status of the job

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

BearerAuth

GET /api/v2/projects/{projectId}/primeModels/{modelId}/

Retrieve a Prime model details

Code samples

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

Parameters

Name In Type Required Description
projectId path string true the project to retrieve the model from
modelId path string true the model to retrieve

Example responses

200 Response

{
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "ruleCount": 0,
  "rulesetId": 0,
  "samplePct": 0,
  "samplingMethod": "random",
  "score": 0,
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Responses

Status Meaning Description Schema
200 OK Prime models are an extension of models, so the response includes all attributes that would be in a response to GET /api/v2/projects/(projectId)/models/(modelId)/ as well as some additional ones. PrimeModelDetailsRetrieveResponse

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

BearerAuth

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

Lists all the models from a project that have rating tables

Code samples

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

Parameters

Name In Type Required Description
withMetric query string false If specified, the returned models will only have scores for this metric. If not, all metrics will be included.
showInSampleScores query boolean false If specified, will return metric scores for models trained into validation/holdout for projects that do not have stacked predictions.
name query string false If specified, filters for models with a model type matching name.
samplePct query number false If specified, filters for models with a matching sample percentage.
isStarred query string false If specified, filters for models marked as starred.
orderBy query string false A comma-separated list of metrics to sort by. If metric is prefixed with a '-', models are sorted by this metric in descending order, otherwise are sorted in ascending order. Valid sorting metrics are metric and samplePct. Use of metric sorts models by metric value selected for this project using the validation score. Use of the prefix accounts for the direction of the metric, so -metric will sort in order of decreasing 'goodness', which may be opposite to the natural numerical order. If not specified, -metric will be used.
projectId path string true the project to list models from

Enumerated Values

Parameter Value
isStarred [false, False, true, True]
orderBy [metric, -metric, samplePct, -samplePct]

Example responses

200 Response

[
  {
    "blueprintId": "string",
    "dataSelectionMethod": "duration",
    "featurelistId": "string",
    "featurelistName": "string",
    "hasFinetuners": true,
    "id": "string",
    "isAugmented": true,
    "isFrozen": true,
    "isNClustersDynamicallyDetermined": true,
    "isStarred": true,
    "isTrainedIntoHoldout": true,
    "isTrainedIntoValidation": true,
    "lifecycle": {
      "reason": "string",
      "stage": "active"
    },
    "linkFunction": "string",
    "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
    "modelCategory": "model",
    "modelFamily": "string",
    "modelFamilyFullName": "string",
    "modelNumber": 0,
    "modelType": "string",
    "monotonicDecreasingFeaturelistId": "string",
    "monotonicIncreasingFeaturelistId": "string",
    "nClusters": 0,
    "parentModelId": "string",
    "predictionThreshold": 1,
    "predictionThresholdReadOnly": true,
    "processes": [
      "string"
    ],
    "projectId": "string",
    "ratingTableId": "string",
    "samplePct": 0,
    "samplingMethod": "random",
    "supportsComposableMl": true,
    "supportsMonotonicConstraints": true,
    "timeWindowSamplePct": 0,
    "trainingDuration": "string",
    "trainingEndDate": "2019-08-24T14:15:22Z",
    "trainingRowCount": 0,
    "trainingStartDate": "2019-08-24T14:15:22Z"
  }
]

Responses

Status Meaning Description Schema
200 OK The response will include a json list of models in the same format as
those from GET /api/v2/projects/(projectId)/ratingTableModels/(modelId)/. Inline

Response Schema

Status Code 200

Name Type Required Restrictions Description
anonymous [RatingTableModelDetailsResponse] false none
» blueprintId string true The blueprint used to construct the model.
» dataSelectionMethod string false Identifies which setting defines the training size of the model when making predictions and scoring. Only used by datetime models.
» featurelistId string¦null true the ID of the featurelist used by the model
» featurelistName string¦null true the name of the featurelist used by the model.If null, the model was trained on multiple feature lists.
» hasFinetuners boolean false Whether a model has fine tuners.
» id string true the ID of the model
» isAugmented boolean false Whether a model was trained using augmentation.
» isFrozen boolean true Indicates whether the model is frozen, i.e., uses tuning parameters from a parent model.
» isNClustersDynamicallyDetermined boolean false Whether number of clusters is dynamically determined. Only valid in unsupervised clustering projects.
» isStarred boolean true whether the model has been starred
» isTrainedIntoHoldout boolean true Indicates if model used holdout data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or whenthe model's training row count was greater than the max allowed validation size.
» isTrainedIntoValidation boolean true Indicates if model used validation data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or when the model's training row count was greater than the max allowed training size.
» lifecycle ModelLifecycle true none
»» reason string¦null true Reason for lifecycle stage. None if model is active.
»» stage string true Model lifecycle stage.
» linkFunction string¦null true The link function the final modeler uses in the blueprint. If no link function exists, returns null.
» metrics object true the performance of the model according to various metrics, where each metric has validation, crossValidation, holdout, and training scores reported, or null if they have not been computed.
» modelCategory string true Indicates the kind of model. Returns prime for DataRobot Prime models, blend for blender models, combined for combined models, and model for all other models.
» modelFamily string true the family model belongs to, e.g. SVM, GBM, etc.
» modelFamilyFullName string true The full name of the family that the model belongs to. For e.g., Support Vector Machine, Gradient Boosting Machine, etc.
» modelNumber integer¦null true minimum: 0 (exclusive)
The model number from the leaderboard.
» modelType string true identifies the model, e.g. Nystroem Kernel SVM Regressor
» monotonicDecreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
» monotonicIncreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
» nClusters integer¦null false The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
» parentModelId string¦null true The ID of the parent model if the model is frozen or a result of incremental learning. Null otherwise.
» predictionThreshold number true maximum: 1
minimum: 0
threshold used for binary classification in predictions.
» predictionThresholdReadOnly boolean true indicates whether modification of a predictions threshold is forbidden. Since v2.22 threshold modification is allowed.
» processes [string]¦null true list of processes used by the model
» projectId string true the ID of the project to which the model belongs
» ratingTableId string true The rating table ID
» samplePct number¦null true minimum: 0 (exclusive)
the percentage of the dataset used in training the model
» samplingMethod string false indicates sampling method used to select training data in datetime models. For row-based project this is the way how requested number of rows are selected.For other projects (duration-based, start/end, project settings) - how specified percent of rows (timeWindowSamplePct) is selected from specified time window.
» supportsComposableMl boolean true indicates whether this model is supported in Composable ML.
» supportsMonotonicConstraints boolean true whether this model supports enforcing monotonic constraints
» timeWindowSamplePct integer¦null false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99, indicating the percentage of sampling within the time window. The points kept are determined by samplingMethod option. Will be null if no sampling was specified. Only used by datetime models.
» trainingDuration string¦null true the duration spanned by the dates in the partition column for the data used to train the model
» trainingEndDate string(date-time)¦null true the end date of the dates in the partition column for the data used to train the model
» trainingRowCount integer¦null true minimum: 0 (exclusive)
The number of rows used to train the model.
» trainingStartDate string(date-time)¦null true the start date of the dates in the partition column for the data used to train the model

Enumerated Values

Property Value
dataSelectionMethod [duration, rowCount, selectedDateRange, useProjectSettings]
stage [active, deprecated, disabled]
modelCategory [model, prime, blend, combined, incrementalLearning]
samplingMethod [random, latest]

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

BearerAuth

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

Create a new rating table model from a validated rating table record

Code samples

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

Body parameter

{
  "ratingTableId": "string"
}

Parameters

Name In Type Required Description
projectId path string true the project that owns this data
body body CreateRatingTableModel false none

Responses

Status Meaning Description Schema
202 Accepted the request was understood and accepted, and is now being worked on None

Response Headers

Status Header Type Format Description
202 Location string url a url of an asynchronous operation status object that can be polled to check the status of the job validating the new rating table

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

BearerAuth

GET /api/v2/projects/{projectId}/ratingTableModels/{modelId}/

Look up a particular rating table model

Code samples

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

Parameters

Name In Type Required Description
projectId path string true the project to retrieve the model from
modelId path string true the model to retrieve

Example responses

200 Response

{
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "ratingTableId": "string",
  "samplePct": 0,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Responses

Status Meaning Description Schema
200 OK none RatingTableModelDetailsResponse

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

BearerAuth

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

List RatingTable objects for a project. These contain metadata about the rating table and the location at which the corresponding rating table file can be retrieved.

Code samples

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

Parameters

Name In Type Required Description
parentModelId query string false optional. If specified, only rating tables with this parentModelId will be returned
modelId query string false optional. If specified, only rating tables with this modelId will be returned
offset query integer false optional (default: 0), this many results will be skipped
limit query integer false optional (default: no limit), at most this many results are returned. To specify no limit, use 0. The default may change and a maximum limit may be imposed without notice.
projectId path string true The project ID

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "created": 0,
      "id": "string",
      "modelId": "string",
      "modelJobId": 0,
      "originalFilename": "string",
      "parentModelId": "string",
      "projectId": "string",
      "ratingTableName": "string",
      "validationError": "string",
      "validationJobId": "string",
      "validationWarnings": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses

Status Meaning Description Schema
200 OK none RatingTableListResponse

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

BearerAuth

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

Create a new rating table from a rating table file This will create a new rating table, regardless of whether the validation succeeds. The rating table object will have a validationError which will be left blank in the case of successful validation.

Code samples

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

Body parameter

parentModelId: string
ratingTableFile: string
ratingTableName: string

Parameters

Name In Type Required Description
projectId path string true the project that owns this data
body body UploadRatingTable false none

Example responses

202 Response

{
  "ratingTableId": "string",
  "ratingTableName": "string"
}

Responses

Status Meaning Description Schema
202 Accepted the request was understood and accepted, and is now being worked on RatingTableCreateResponse

Response Headers

Status Header Type Format Description
202 Location string url a url of an asynchronous operation status object that can be polled to check the status of the job validating the new rating table

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

BearerAuth

GET /api/v2/projects/{projectId}/ratingTables/{ratingTableId}/

Retrieves a rating table

Code samples

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

Parameters

Name In Type Required Description
projectId path string true the project that owns this data
ratingTableId path string true the rating table ID to retrieve the source file from

Example responses

200 Response

{
  "created": 0,
  "id": "string",
  "modelId": "string",
  "modelJobId": 0,
  "originalFilename": "string",
  "parentModelId": "string",
  "projectId": "string",
  "ratingTableName": "string",
  "validationError": "string",
  "validationJobId": "string",
  "validationWarnings": "string"
}

Responses

Status Meaning Description Schema
200 OK none RatingTableRetrieveResponse

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

BearerAuth

PATCH /api/v2/projects/{projectId}/ratingTables/{ratingTableId}/

Rating tables may only be updated if they have not yet been used to create a model.

Code samples

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

Body parameter

{
  "ratingTableName": "string"
}

Parameters

Name In Type Required Description
projectId path string true the project that owns this data
ratingTableId path string true the rating table ID to retrieve the source file from
body body RatingTableUpdate false none

Example responses

200 Response

{
  "created": 0,
  "id": "string",
  "modelId": "string",
  "modelJobId": 0,
  "originalFilename": "string",
  "parentModelId": "string",
  "projectId": "string",
  "ratingTableName": "string",
  "validationError": "string",
  "validationJobId": "string",
  "validationWarnings": "string"
}

Responses

Status Meaning Description Schema
200 OK On success, will return the modified rating table record in the same
format as GET /api/v2/projects/(projectId)/ratingTables/(ratingTableId)/ RatingTableRetrieveResponse

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

BearerAuth

GET /api/v2/projects/{projectId}/ratingTables/{ratingTableId}/file/

Retrieve the CSV file for the rating table

Code samples

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

Parameters

Name In Type Required Description
projectId path string true the project that owns this data
ratingTableId path string true the rating table ID to retrieve the source file from

Responses

Status Meaning Description Schema
200 OK The response will contain a file containing the rating table in csv format None

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

BearerAuth

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

Retrieves all of the current recommended models for the project

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/recommendedModels/ \
  -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

[
  {
    "modelId": "string",
    "recommendationType": "MOSTACCURATE"
  }
]

Responses

Status Meaning Description Schema
200 OK The list of recommended models Inline

Response Schema

Status Code 200

Name Type Required Restrictions Description
anonymous [RecommendedModelResponse] false none
» modelId string true the ID of the recommended model
» recommendationType string true the type of model recommendation

Enumerated Values

Property Value
recommendationType [MOSTACCURATE, LIMITEDACCURATE, FASTACCURATE, RECOMMENDEDFORDEPLOYMENT, PREPAREDFORDEPLOYMENT]

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

BearerAuth

GET /api/v2/projects/{projectId}/recommendedModels/recommendedModel/

This route returns the simplest recommended model available. To see all the available recommended models, use GET /api/v2/projects/{projectId}/recommendedModels/

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/recommendedModels/recommendedModel/ \
  -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

{
  "modelId": "string",
  "recommendationType": "MOSTACCURATE"
}

Responses

Status Meaning Description Schema
200 OK The recommended model RecommendedModelResponse

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

BearerAuth

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

List all RuleFit code files available for download

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/ruleFitFiles/?offset=0&limit=100 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
modelId query string false if specified only RuleFit code files with code used in the specified RuleFit model will be returned; otherwise all applicable RuleFit files will be returned
offset query integer true This many files will be skipped.
limit query integer true At most this many files are returned.
projectId path string true the project to list available files for

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "id": "string",
      "isValid": true,
      "language": "Python",
      "modelId": "string",
      "projectId": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses

Status Meaning Description Schema
200 OK none RuleFitCodeFileListResponse

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

BearerAuth

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

Request creation and validation of source code from a RuleFit model

Code samples

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

Body parameter

{
  "language": "Python",
  "modelId": "string"
}

Parameters

Name In Type Required Description
projectId path string true the project the file belongs to
body body RuleFitCodeFileCreate false none

Responses

Status Meaning Description Schema
202 Accepted RuleFit code validation job added to queue. See the Location header. None

Response Headers

Status Header Type Format Description
202 Location string url a url that can be polled to check the status of RuleFit code validation job

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

BearerAuth

GET /api/v2/projects/{projectId}/ruleFitFiles/{ruleFitFileId}/

Get information about a RuleFit code file available for download

Code samples

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

Parameters

Name In Type Required Description
ruleFitFileId path string true the ID of the file
projectId path string true the project to list available files for

Example responses

200 Response

{
  "id": "string",
  "isValid": true,
  "language": "Python",
  "modelId": "string",
  "projectId": "string"
}

Responses

Status Meaning Description Schema
200 OK none RuleFitCodeFileResponse

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

BearerAuth

GET /api/v2/projects/{projectId}/ruleFitFiles/{ruleFitFileId}/download/

Download code from an existing RuleFit file

Code samples

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

Parameters

Name In Type Required Description
ruleFitFileId path string true the ID of the file
projectId path string true the project to list available files for

Responses

Status Meaning Description Schema
200 OK The response will contain a file with the executable code from the RuleFit model None

Response Headers

Status Header Type Format Description
200 Content-Disposition string Will be attachment;filename="<"filename">". The suggested filename will depend on the language RuleFit file was generated for.

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

BearerAuth

PUT /api/v2/projects/{projectId}/segmentChampion/

Update champion model for a segment project.

Code samples

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

Body parameter

{
  "clone": false,
  "modelId": "string"
}

Parameters

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

Example responses

200 Response

{
  "combinedModelId": "string"
}

Responses

Status Meaning Description Schema
200 OK The ID of Combined model that has been updated with new segment champion model. SegmentChampionModelUpdateResponse

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

BearerAuth

GET /api/v2/registeredModels/

List registered models.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/registeredModels/ \
  -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.
search query string false A term to search for in registered model name
createdAtStartTs query string(date-time) false Registered models created on or after this timestamp
createdAtEndTs query string(date-time) false Registered models created before this timestamp. Defaults to the current time
modifiedAtStartTs query string(date-time) false Registered models modified on or after this timestamp
modifiedAtEndTs query string(date-time) false Registered models modified before this timestamp. Defaults to the current time
targetName query string false Name of the target to filter by
targetType query string false Type of the target to filter by
createdBy query string false Email of the user that created registered model to filter by
sortKey query string false Key to order result by
sortDirection query string false Sort direction
compatibleWithLeaderboardModelId query string false If specified, limit results to registered models containing versions (model packages) for the leaderboard model with the specified ID.
compatibleWithModelPackageId query string false Return registered models that have versions (model packages) compatible with given model package ID. If used, will only return registered models which have versions that match target.name, target.type, target.classNames (for classification models), modelKind.isTimeSeries, and modelKind.isMultiseries of the specified model package.
forChallenger query boolean false Can be used with compatibleWithModelPackageId to request similar registered models that contain versions (model packages)that can be used as challenger models; for external model packages, instead of returning similar external model packages, similar DataRobot and Custom model packages will be retrieved.
predictionThreshold query number false If specified, return any registered models containing one or more versions matching the prediction threshold used for binary classification models
imported query boolean false If specified, return any registered models that contain either imported (true) or non-imported (false) versions (model packages)
predictionEnvironmentId query string false Can be used to filter registered models by what is supported by the prediction environment
modelKind query any false Return models that contain versions matching a specific format
buildStatus query string false If specified, only return models that have versions with specified build status
isGlobal query boolean false Return only global (accessible to all users in the organization) registered models or local(accessible only to the owner and the users with whom it has been explicitly shared)
tagKeys query string false List of tag keys to filter by.
tagValues query string false List of tag values to filter by.

Enumerated Values

Parameter Value
sortKey [createdAt, modifiedAt, name]
sortDirection [asc, desc]
buildStatus [inProgress, complete, failed]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "createdAt": "2019-08-24T14:15:22Z",
      "createdBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "description": "string",
      "id": "string",
      "isArchived": true,
      "isGlobal": true,
      "lastVersionNum": 0,
      "modifiedAt": "2019-08-24T14:15:22Z",
      "modifiedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "name": "string",
      "target": {
        "name": "string",
        "type": "string"
      }
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK none RegisteredModelListResponse

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

BearerAuth

DELETE /api/v2/registeredModels/{registeredModelId}/

Permanently archive a registered model and all of its versions

Code samples

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

Parameters

Name In Type Required Description
registeredModelId path string true ID of the registered model.

Responses

Status Meaning Description Schema
204 No Content none None

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

BearerAuth

GET /api/v2/registeredModels/{registeredModelId}/

Retrieve info about a registered model.

Code samples

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

Parameters

Name In Type Required Description
registeredModelId path string true ID of the registered model.

Example responses

200 Response

{
  "createdAt": "2019-08-24T14:15:22Z",
  "createdBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "description": "string",
  "id": "string",
  "isArchived": true,
  "isGlobal": true,
  "lastVersionNum": 0,
  "modifiedAt": "2019-08-24T14:15:22Z",
  "modifiedBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "name": "string",
  "target": {
    "name": "string",
    "type": "string"
  }
}

Responses

Status Meaning Description Schema
200 OK none RegisteredModelResponse
404 Not Found The registered model does not exist or the user does not have permission to view the model package. None

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

BearerAuth

PATCH /api/v2/registeredModels/{registeredModelId}/

Update registered model

Code samples

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

Body parameter

{
  "description": "string",
  "isGlobal": true,
  "name": "string"
}

Parameters

Name In Type Required Description
registeredModelId path string true ID of the registered model.
body body RegisteredModelUpdate false none

Responses

Status Meaning Description Schema
200 OK none None
422 Unprocessable Entity Unable to process the Registered Model update request None

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

BearerAuth

GET /api/v2/registeredModels/{registeredModelId}/deployments/

List deployments associated with the given registered model

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/registeredModels/{registeredModelId}/deployments/ \
  -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.
search query string false Filter deployments with name matching search term
sortKey query string false Key to order result by
sortDirection query string false Sort direction
registeredModelId path string true ID of the registered model.

Enumerated Values

Parameter Value
sortKey [createdAt, label]
sortDirection [asc, desc]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "createdAt": "string",
      "createdBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "currentlyDeployed": true,
      "firstDeployedAt": "string",
      "firstDeployedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "id": "string",
      "isChallenger": true,
      "label": "string",
      "predictionEnvironment": {
        "id": "string",
        "isManagedByManagementAgent": true,
        "name": "string",
        "platform": "aws",
        "plugin": "string",
        "supportedModelFormats": [
          "datarobot"
        ]
      },
      "registeredModelVersion": 0,
      "status": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK none RegisteredModelDeploymentsListResponse

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

BearerAuth

GET /api/v2/registeredModels/{registeredModelId}/sharedRoles/

Get a list of users, groups and organizations who have access to this registered model and their roles on the registered model.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/registeredModels/{registeredModelId}/sharedRoles/?offset=0&limit=10 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
id query string false Only return roles for a user, group or organization with this identifier.
offset query integer true This many results will be skipped
limit query integer true At most this many results are returned
name query string false Only return roles for a user, group or organization with this name.
shareRecipientType query string false List access controls for recipients with this type.
registeredModelId path string true ID of the registered model.

Enumerated Values

Parameter Value
shareRecipientType [user, group, organization]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "id": "string",
      "name": "string",
      "role": "ADMIN",
      "shareRecipientType": "user"
    }
  ],
  "next": "string",
  "previous": "string",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK The registered model's access control list. SharingListV2Response
404 Not Found Either the Registered Model does not exist or the user does not have permissions to view the Registered Model. None
422 Unprocessable Entity Both username and userId were specified None

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

BearerAuth

PATCH /api/v2/registeredModels/{registeredModelId}/sharedRoles/

Set roles for users on this registered model.

Code samples

# You can also use wget
curl -X PATCH https://app.datarobot.com/api/v2/registeredModels/{registeredModelId}/sharedRoles/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}"

Body parameter

{
  "operation": "updateRoles",
  "roles": [
    {
      "role": "string",
      "shareRecipientType": "user",
      "username": "string"
    }
  ]
}

Parameters

Name In Type Required Description
registeredModelId path string true ID of the registered model.
body body SharedRolesUpdate false none

Responses

Status Meaning Description Schema
204 No Content Roles updated successfully. None
409 Conflict The request would leave the registered model without an owner. None
422 Unprocessable Entity One of the users in the request does not exist, or the request is otherwise invalid None

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

BearerAuth

GET /api/v2/registeredModels/{registeredModelId}/versions/

List registered model's versions.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/registeredModels/{registeredModelId}/versions/ \
  -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.
sortKey query string false Key to order result by
sortDirection query string false Sort direction
targetName query string false Name of the target to filter by
targetType query string false Type of the target to filter by
search query string false A term to search for in version name, model name, or description
compatibleWithLeaderboardModelId query string false If specified, limit results to versions (model packages) of the leaderboard model with the specified ID.
compatibleWithModelPackageId query string false Return versions compatible with given model package ID. If used, will only return versions that match target.name, target.type, target.classNames (for classification models), modelKind.isTimeSeries, and modelKind.isMultiseries of the specified model package
forChallenger query boolean false Can be used with compatibleWithModelPackageId to request similar versions that can be used as challenger models; for external model packages, instead of returning similar external model packages, similar DataRobot and Custom model packages will be retrieved
predictionThreshold query number false Return versions with the specified prediction threshold used for binary classification models
imported query boolean false If specified, return either imported (true) or non-imported (false) versions (model packages)
predictionEnvironmentId query string false Can be used to filter versions (model packages) by what is supported by the prediction environment
modelKind query any false Return versions that match a specific format.
buildStatus query string false If specified, filter versions by the build status.
useCaseId query string false If specified, filter versions by use-case id.
createdBy query string false Email of the user that created registered model version to filter by
registeredModelId path string true ID of the registered model.

Enumerated Values

Parameter Value
sortKey [version, modelType, status, createdAt, updatedAt]
sortDirection [asc, desc]
buildStatus [inProgress, complete, failed]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "activeDeploymentCount": 0,
      "buildStatus": "inProgress",
      "capabilities": {
        "supportsAutomaticActuals": true,
        "supportsChallengerModels": true,
        "supportsFeatureDriftTracking": true,
        "supportsHumilityRecommendedRules": true,
        "supportsHumilityRules": true,
        "supportsHumilityRulesDefaultCalculations": true,
        "supportsPredictionWarning": true,
        "supportsRetraining": true,
        "supportsScoringCodeDownload": true,
        "supportsSecondaryDatasets": true,
        "supportsSegmentedAnalysisDriftAndAccuracy": true,
        "supportsShapBasedPredictionExplanations": true,
        "supportsTargetDriftTracking": true
      },
      "datasets": {
        "baselineSegmentedBy": [
          "string"
        ],
        "datasetName": "string",
        "holdoutDataCatalogId": "string",
        "holdoutDataCatalogVersionId": "string",
        "holdoutDatasetName": "string",
        "targetHistogramBaseline": "predictions",
        "trainingDataCatalogId": "string",
        "trainingDataCatalogVersionId": "string",
        "trainingDataSize": 0
      },
      "id": "string",
      "importMeta": {
        "containsFearPipeline": true,
        "containsFeaturelists": true,
        "containsLeaderboardMeta": true,
        "containsProjectMeta": true,
        "creatorFullName": "string",
        "creatorId": "string",
        "creatorUsername": "string",
        "dateCreated": "string",
        "originalFileName": "string"
      },
      "isArchived": true,
      "isDeprecated": true,
      "mlpkgFileContents": {
        "allTimeSeriesPredictionIntervals": true
      },
      "modelDescription": {
        "buildEnvironmentType": "DataRobot",
        "description": "string",
        "location": "string",
        "modelCreatedAt": "string",
        "modelCreatorEmail": "string",
        "modelCreatorId": null,
        "modelCreatorName": "string",
        "modelName": "string"
      },
      "modelExecutionType": "dedicated",
      "modelId": "string",
      "modelKind": {
        "isAnomalyDetectionModel": true,
        "isCombinedModel": true,
        "isDecisionFlow": true,
        "isFeatureDiscovery": true,
        "isMultiseries": true,
        "isTimeSeries": true,
        "isUnsupervisedLearning": true
      },
      "name": "string",
      "permissions": [
        "string"
      ],
      "sourceMeta": {
        "decisionFlowId": "string",
        "decisionFlowVersionId": "string",
        "environmentUrl": "http://example.com",
        "fips_140_2Enabled": true,
        "projectCreatedAt": "string",
        "projectCreatorEmail": "string",
        "projectCreatorId": null,
        "projectCreatorName": "string",
        "projectId": "string",
        "projectName": "string",
        "scoringCode": {
          "dataRobotPredictionVersion": "string",
          "location": "local_leaderboard"
        },
        "useCaseDetails": {
          "createdAt": "string",
          "creatorEmail": "string",
          "creatorId": "string",
          "creatorName": "string",
          "id": "string",
          "name": "string"
        }
      },
      "target": {
        "classCount": 0,
        "classNames": [
          "string"
        ],
        "name": "string",
        "predictionProbabilitiesColumn": "string",
        "predictionThreshold": 1,
        "type": "Binary"
      },
      "timeseries": {
        "datetimeColumnFormat": "string",
        "datetimeColumnName": "string",
        "effectiveFeatureDerivationWindowEnd": 0,
        "effectiveFeatureDerivationWindowStart": 0,
        "featureDerivationWindowEnd": 0,
        "featureDerivationWindowStart": 0,
        "forecastDistanceColumnName": "string",
        "forecastDistances": [
          0
        ],
        "forecastDistancesTimeUnit": "MICROSECOND",
        "forecastPointColumnName": "string",
        "isCrossSeries": true,
        "isNewSeriesSupport": true,
        "isTraditionalTimeSeries": true,
        "seriesColumnName": "string"
      },
      "updatedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "userProvidedId": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK none RegisteredModelVersionsListResponse

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

BearerAuth

GET /api/v2/registeredModels/{registeredModelId}/versions/{versionId}/

Get a registered model's version.

Code samples

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

Parameters

Name In Type Required Description
registeredModelId path string true ID of the registered model.
versionId path string true ID of the registered model's version.

Example responses

200 Response

{
  "activeDeploymentCount": 0,
  "buildStatus": "inProgress",
  "capabilities": {
    "supportsAutomaticActuals": true,
    "supportsChallengerModels": true,
    "supportsFeatureDriftTracking": true,
    "supportsHumilityRecommendedRules": true,
    "supportsHumilityRules": true,
    "supportsHumilityRulesDefaultCalculations": true,
    "supportsPredictionWarning": true,
    "supportsRetraining": true,
    "supportsScoringCodeDownload": true,
    "supportsSecondaryDatasets": true,
    "supportsSegmentedAnalysisDriftAndAccuracy": true,
    "supportsShapBasedPredictionExplanations": true,
    "supportsTargetDriftTracking": true
  },
  "datasets": {
    "baselineSegmentedBy": [
      "string"
    ],
    "datasetName": "string",
    "holdoutDataCatalogId": "string",
    "holdoutDataCatalogVersionId": "string",
    "holdoutDatasetName": "string",
    "targetHistogramBaseline": "predictions",
    "trainingDataCatalogId": "string",
    "trainingDataCatalogVersionId": "string",
    "trainingDataSize": 0
  },
  "id": "string",
  "importMeta": {
    "containsFearPipeline": true,
    "containsFeaturelists": true,
    "containsLeaderboardMeta": true,
    "containsProjectMeta": true,
    "creatorFullName": "string",
    "creatorId": "string",
    "creatorUsername": "string",
    "dateCreated": "string",
    "originalFileName": "string"
  },
  "isArchived": true,
  "isDeprecated": true,
  "mlpkgFileContents": {
    "allTimeSeriesPredictionIntervals": true
  },
  "modelDescription": {
    "buildEnvironmentType": "DataRobot",
    "description": "string",
    "location": "string",
    "modelCreatedAt": "string",
    "modelCreatorEmail": "string",
    "modelCreatorId": null,
    "modelCreatorName": "string",
    "modelName": "string"
  },
  "modelExecutionType": "dedicated",
  "modelId": "string",
  "modelKind": {
    "isAnomalyDetectionModel": true,
    "isCombinedModel": true,
    "isDecisionFlow": true,
    "isFeatureDiscovery": true,
    "isMultiseries": true,
    "isTimeSeries": true,
    "isUnsupervisedLearning": true
  },
  "name": "string",
  "permissions": [
    "string"
  ],
  "sourceMeta": {
    "decisionFlowId": "string",
    "decisionFlowVersionId": "string",
    "environmentUrl": "http://example.com",
    "fips_140_2Enabled": true,
    "projectCreatedAt": "string",
    "projectCreatorEmail": "string",
    "projectCreatorId": null,
    "projectCreatorName": "string",
    "projectId": "string",
    "projectName": "string",
    "scoringCode": {
      "dataRobotPredictionVersion": "string",
      "location": "local_leaderboard"
    },
    "useCaseDetails": {
      "createdAt": "string",
      "creatorEmail": "string",
      "creatorId": "string",
      "creatorName": "string",
      "id": "string",
      "name": "string"
    }
  },
  "target": {
    "classCount": 0,
    "classNames": [
      "string"
    ],
    "name": "string",
    "predictionProbabilitiesColumn": "string",
    "predictionThreshold": 1,
    "type": "Binary"
  },
  "timeseries": {
    "datetimeColumnFormat": "string",
    "datetimeColumnName": "string",
    "effectiveFeatureDerivationWindowEnd": 0,
    "effectiveFeatureDerivationWindowStart": 0,
    "featureDerivationWindowEnd": 0,
    "featureDerivationWindowStart": 0,
    "forecastDistanceColumnName": "string",
    "forecastDistances": [
      0
    ],
    "forecastDistancesTimeUnit": "MICROSECOND",
    "forecastPointColumnName": "string",
    "isCrossSeries": true,
    "isNewSeriesSupport": true,
    "isTraditionalTimeSeries": true,
    "seriesColumnName": "string"
  },
  "updatedBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "userProvidedId": "string"
}

Responses

Status Meaning Description Schema
200 OK none ModelPackageRetrieveResponse

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

BearerAuth

GET /api/v2/registeredModels/{registeredModelId}/versions/{versionId}/deployments/

List all deployments associated with registered model version.

Code samples

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/registeredModels/{registeredModelId}/versions/{versionId}/deployments/ \
  -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.
search query string false Filter deployments with name matching search term
sortKey query string false Key to order result by
sortDirection query string false Sort direction
registeredModelId path string true ID of the registered model.
versionId path string true ID of the registered model's version.

Enumerated Values

Parameter Value
sortKey [createdAt, label]
sortDirection [asc, desc]

Example responses

200 Response

{
  "count": 0,
  "data": [
    {
      "createdAt": "string",
      "createdBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "currentlyDeployed": true,
      "firstDeployedAt": "string",
      "firstDeployedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "id": "string",
      "isChallenger": true,
      "label": "string",
      "predictionEnvironment": {
        "id": "string",
        "isManagedByManagementAgent": true,
        "name": "string",
        "platform": "aws",
        "plugin": "string",
        "supportedModelFormats": [
          "datarobot"
        ]
      },
      "registeredModelVersion": 0,
      "status": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Responses

Status Meaning Description Schema
200 OK none RegisteredModelDeploymentsListResponse

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

BearerAuth

Schemas

AccessControl

{
  "canShare": true,
  "role": "string",
  "userId": "string",
  "username": "string"
}

Properties

Name Type Required Restrictions Description
canShare boolean true Whether the recipient can share the role further.
role string true The role of the user on this entity.
userId string true The identifier of the user that has access to this entity.
username string true The username of the user that has access to the entity.

AccessControlV2

{
  "id": "string",
  "name": "string",
  "role": "ADMIN",
  "shareRecipientType": "user"
}

Properties

Name Type Required Restrictions Description
id string true The identifier of the recipient.
name string true The name of the recipient.
role string true The role of the recipient on this entity.
shareRecipientType string true The type of the recipient.

Enumerated Values

Property Value
role [ADMIN, CONSUMER, DATA_SCIENTIST, EDITOR, OBSERVER, OWNER, READ_ONLY, READ_WRITE, USER]
shareRecipientType [user, group, organization]

AdvancedTuningArgumentsRetrieveResponse

{
  "tuningDescription": "string",
  "tuningParameters": [
    {
      "constraints": {
        "ascii": {
          "supportsGridSearch": true
        },
        "float": {
          "max": 0,
          "min": 0,
          "supportsGridSearch": true
        },
        "floatList": {
          "maxLength": 0,
          "maxVal": 0,
          "minLength": 0,
          "minVal": 0,
          "supportsGridSearch": true
        },
        "int": {
          "max": 0,
          "min": 0,
          "supportsGridSearch": true
        },
        "intList": {
          "maxLength": 0,
          "maxVal": 0,
          "minLength": 0,
          "minVal": 0,
          "supportsGridSearch": true
        },
        "select": {
          "supportsGridSearch": true,
          "values": [
            "string"
          ]
        },
        "selectgrid": {
          "supportsGridSearch": true,
          "values": [
            "string"
          ]
        },
        "unicode": {
          "supportsGridSearch": true
        }
      },
      "currentValue": "string",
      "defaultValue": "string",
      "parameterId": "string",
      "parameterName": "string",
      "taskName": "string",
      "vertexId": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
tuningDescription string¦null true Human-readable description of the tuned model, if specified by the user. null if unspecified.
tuningParameters [TuningParameters] true An array of objects containing information about tuning parameters that are supported by the specified model.

BacktestStatusResponse

{
  "index": 0,
  "score": 0,
  "status": "COMPLETED",
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Properties

Name Type Required Restrictions Description
index integer true the index of the fold
score number¦null true the score of the model for this backtesting fold, if computed
status string true the status of the current backtest model job
trainingDuration string(duration) true the duration of the data used to train the model for this backtesting fold
trainingEndDate string(date-time) true the end date of the training for this backtesting fold
trainingRowCount integer true the number of rows used to train the model for this backtesting fold
trainingStartDate string(date-time) true the start date of the training for this backtesting fold

Enumerated Values

Property Value
status [COMPLETED, NOT_COMPLETED, INSUFFICIENT_DATA, ERRORED, BACKTEST_BOUNDARIES_EXCEEDED]

BaseConstraintType

{
  "supportsGridSearch": true
}

Properties

Name Type Required Restrictions Description
supportsGridSearch boolean true When True, Grid Search is supported for this parameter.

BaseDependencyBuildMetadataResponse

{
  "buildEnd": "string",
  "buildLogLocation": "http://example.com",
  "buildStart": "string",
  "buildStatus": "submitted"
}

Properties

Name Type Required Restrictions Description
buildEnd string¦null true The ISO-8601 encoded time when this build completed.
buildLogLocation string(uri)¦null true The URL to download the build logs from this build.
buildStart string true The ISO-8601 encoded time when this build started.
buildStatus string true The current status of the dependency build.

Enumerated Values

Property Value
buildStatus [submitted, processing, failed, success]

BiasMitigatedModelsDataResponse

{
  "biasMitigationTechnique": "preprocessingReweighing",
  "includeBiasMitigationFeatureAsPredictorVariable": true,
  "modelId": "string",
  "parentModelId": "string",
  "protectedFeature": "string"
}

Properties

Name Type Required Restrictions Description
biasMitigationTechnique string true Method applied to perform bias mitigation.
includeBiasMitigationFeatureAsPredictorVariable boolean true Specifies whether the mitigation feature will be used as a predictor variable (i.e., treated like other categorical features in the input to train the modeler), in addition to being used for bias mitigation. If false, the mitigation feature will be used only for bias mitigation, and not for training the modeler task.
modelId string true Mitigated model ID
parentModelId string¦null true Parent model ID
protectedFeature string true Protected feature that will be used in a bias mitigation task to mitigate bias

Enumerated Values

Property Value
biasMitigationTechnique [preprocessingReweighing, postProcessingRejectionOptionBasedClassification]

BiasMitigatedModelsListResponse

{
  "count": 0,
  "data": [
    {
      "biasMitigationTechnique": "preprocessingReweighing",
      "includeBiasMitigationFeatureAsPredictorVariable": true,
      "modelId": "string",
      "parentModelId": "string",
      "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 [BiasMitigatedModelsDataResponse] true Retrieve list of mitigated models for 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 The total number of items across all pages.

BiasMitigationModelCreate

{
  "biasMitigationFeature": "string",
  "biasMitigationParentLid": "string",
  "biasMitigationTechnique": "preprocessingReweighing",
  "includeBiasMitigationFeatureAsPredictorVariable": true
}

Properties

Name Type Required Restrictions Description
biasMitigationFeature string true minLength: 1
minLength: 1
The name of the protected feature used to mitigate bias on models.
biasMitigationParentLid string true The ID of the model to modify with a bias-mitigation task.
biasMitigationTechnique string true Method applied to perform bias mitigation.
includeBiasMitigationFeatureAsPredictorVariable boolean true Specifies whether the mitigation feature will be used as a predictor variable (i.e., treated like other categorical features in the input to train the modeler), in addition to being used for bias mitigation. If false, the mitigation feature will be used only for bias mitigation, and not for training the modeler task.

Enumerated Values

Property Value
biasMitigationTechnique [preprocessingReweighing, postProcessingRejectionOptionBasedClassification]

BlenderCreate

{
  "blenderMethod": "PLS",
  "modelIds": [
    "string"
  ]
}

Properties

Name Type Required Restrictions Description
blenderMethod string true The blender method, one of "PLS", "GLM", "AVG", "ENET", "MED", "MAE", "MAEL1", "TF", "RF", "LGBM", "FORECAST_DISTANCE_ENET" (new in v2.18), "FORECAST_DISTANCE_AVG" (new in v2.18), "MIN", "MAX".
modelIds [string] true minItems: 1
The list of models to use in blender.

Enumerated Values

Property Value
blenderMethod [PLS, GLM, ENET, AVG, MED, MAE, MAEL1, FORECAST_DISTANCE_AVG, FORECAST_DISTANCE_ENET, MAX, MIN]

BlenderInfoRetrieveResponse

{
  "blendable": true,
  "reason": "string"
}

Properties

Name Type Required Restrictions Description
blendable boolean true If True, the models can be blended.
reason string true Useful info as to why a model can't be blended.

BlenderListResponse

{
  "count": 0,
  "data": [
    {
      "blenderMethod": "string",
      "blueprintId": "string",
      "dataSelectionMethod": "duration",
      "featurelistId": "string",
      "featurelistName": "string",
      "hasFinetuners": true,
      "id": "string",
      "isAugmented": true,
      "isFrozen": true,
      "isNClustersDynamicallyDetermined": true,
      "isStarred": true,
      "isTrainedIntoHoldout": true,
      "isTrainedIntoValidation": true,
      "lifecycle": {
        "reason": "string",
        "stage": "active"
      },
      "linkFunction": "string",
      "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
      "modelCategory": "model",
      "modelFamily": "string",
      "modelFamilyFullName": "string",
      "modelIds": [
        "string"
      ],
      "modelNumber": 0,
      "modelType": "string",
      "monotonicDecreasingFeaturelistId": "string",
      "monotonicIncreasingFeaturelistId": "string",
      "nClusters": 0,
      "parentModelId": "string",
      "predictionThreshold": 1,
      "predictionThresholdReadOnly": true,
      "processes": [
        "string"
      ],
      "projectId": "string",
      "samplePct": 0,
      "samplingMethod": "random",
      "supportsComposableMl": true,
      "supportsMonotonicConstraints": true,
      "timeWindowSamplePct": 0,
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties

Name Type Required Restrictions Description
count integer true Number of items returned on this page.
data [BlenderRetrieveResponse] true Each has the same schema as if retrieving the model individually from GET /api/v2/projects/{projectId}/blenderModels/{modelId}/.
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).

BlenderRetrieveResponse

{
  "blenderMethod": "string",
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelIds": [
    "string"
  ],
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": 0,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Properties

Name Type Required Restrictions Description
blenderMethod string true Method used to blend results of underlying models.
blueprintId string true The blueprint used to construct the model.
dataSelectionMethod string false Identifies which setting defines the training size of the model when making predictions and scoring. Only used by datetime models.
featurelistId string¦null true the ID of the featurelist used by the model
featurelistName string¦null true the name of the featurelist used by the model.If null, the model was trained on multiple feature lists.
hasFinetuners boolean false Whether a model has fine tuners.
id string true the ID of the model
isAugmented boolean false Whether a model was trained using augmentation.
isFrozen boolean true Indicates whether the model is frozen, i.e., uses tuning parameters from a parent model.
isNClustersDynamicallyDetermined boolean false Whether number of clusters is dynamically determined. Only valid in unsupervised clustering projects.
isStarred boolean true whether the model has been starred
isTrainedIntoHoldout boolean true Indicates if model used holdout data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or whenthe model's training row count was greater than the max allowed validation size.
isTrainedIntoValidation boolean true Indicates if model used validation data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or when the model's training row count was greater than the max allowed training size.
lifecycle ModelLifecycle true Object returning model lifecycle.
linkFunction string¦null true The link function the final modeler uses in the blueprint. If no link function exists, returns null.
metrics object true the performance of the model according to various metrics, where each metric has validation, crossValidation, holdout, and training scores reported, or null if they have not been computed.
modelCategory string true Indicates the kind of model. Returns prime for DataRobot Prime models, blend for blender models, combined for combined models, and model for all other models.
modelFamily string true the family model belongs to, e.g. SVM, GBM, etc.
modelFamilyFullName string true The full name of the family that the model belongs to. For e.g., Support Vector Machine, Gradient Boosting Machine, etc.
modelIds [string] true List of models used in blender.
modelNumber integer¦null true minimum: 0 (exclusive)
The model number from the leaderboard.
modelType string true identifies the model, e.g. Nystroem Kernel SVM Regressor
monotonicDecreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
monotonicIncreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
nClusters integer¦null false The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
parentModelId string¦null true The ID of the parent model if the model is frozen or a result of incremental learning. Null otherwise.
predictionThreshold number true maximum: 1
minimum: 0
threshold used for binary classification in predictions.
predictionThresholdReadOnly boolean true indicates whether modification of a predictions threshold is forbidden. Since v2.22 threshold modification is allowed.
processes [string]¦null true list of processes used by the model
projectId string true the ID of the project to which the model belongs
samplePct number¦null true minimum: 0 (exclusive)
the percentage of the dataset used in training the model
samplingMethod string false indicates sampling method used to select training data in datetime models. For row-based project this is the way how requested number of rows are selected.For other projects (duration-based, start/end, project settings) - how specified percent of rows (timeWindowSamplePct) is selected from specified time window.
supportsComposableMl boolean true indicates whether this model is supported in Composable ML.
supportsMonotonicConstraints boolean true whether this model supports enforcing monotonic constraints
timeWindowSamplePct integer¦null false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99, indicating the percentage of sampling within the time window. The points kept are determined by samplingMethod option. Will be null if no sampling was specified. Only used by datetime models.
trainingDuration string¦null true the duration spanned by the dates in the partition column for the data used to train the model
trainingEndDate string(date-time)¦null true the end date of the dates in the partition column for the data used to train the model
trainingRowCount integer¦null true minimum: 0 (exclusive)
The number of rows used to train the model.
trainingStartDate string(date-time)¦null true the start date of the dates in the partition column for the data used to train the model

Enumerated Values

Property Value
dataSelectionMethod [duration, rowCount, selectedDateRange, useProjectSettings]
modelCategory [model, prime, blend, combined, incrementalLearning]
samplingMethod [random, latest]

ClassificationBinDataResponse

{
  "binEnd": 0,
  "binStart": 0,
  "negatives": 0,
  "positives": 0
}

Properties

Name Type Required Restrictions Description
binEnd number true The end of the numeric range for the current bin. Note that binEnd - binStart should be a constant, modulo floating-point rounding error, for all bins in a single plot.
binStart number true The start of the numeric range for the current bin. Must be equal to the binEnd of the previous bin.
negatives integer true The number of records in the dataset where the model's predicted value falls into this bin and the target is negative.
positives integer true The number of records in the dataset where the model's predicted value falls into this bin and the target is positive.

ClusterInfoList

{
  "name": "string",
  "percent": 100
}

Properties

Name Type Required Restrictions Description
name string true maxLength: 50
minLength: 1
minLength: 1
A cluster name.
percent number false maximum: 100
minimum: 0
The percentage of rows in the dataset this cluster contains.

ClusterNamesMappingValidation

{
  "currentName": "string",
  "newName": "string"
}

Properties

Name Type Required Restrictions Description
currentName string true maxLength: 50
minLength: 1
minLength: 1
Current cluster name.
newName string true maxLength: 50
minLength: 1
minLength: 1
New cluster name.

ClusterNamesResponse

{
  "clusters": [
    {
      "name": "string",
      "percent": 100
    },
    {
      "name": "string",
      "percent": 100
    }
  ],
  "modelId": "string",
  "projectId": "string"
}

Properties

Name Type Required Restrictions Description
clusters [ClusterInfoList] true maxItems: 100
minItems: 2
A list of the model's cluster information entries.
modelId string true The model ID
projectId string true The project ID

ClusterNamesUpdateParam

{
  "clusterNameMappings": [
    {
      "currentName": "string",
      "newName": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
clusterNameMappings [ClusterNamesMappingValidation] true maxItems: 100
A list of the mappings from a cluster's current name to its new name.
After update, value passed as a new name will become cluster's current name.
All cluster names should be unique and should identify one and only one cluster.

CombinedModelListResponse

{
  "count": 0,
  "data": [
    {
      "combinedModelId": "string",
      "isActiveCombinedModel": false,
      "modelCategory": "combined",
      "projectId": "string",
      "segmentationTaskId": "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 [CommonGetAndListCombinedModel] true List of combined models.
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.

CombinedModelResponse

{
  "combinedModelId": "string",
  "isActiveCombinedModel": false,
  "modelCategory": "combined",
  "projectId": "string",
  "segmentationTaskId": "string",
  "segments": [
    {
      "modelId": "string",
      "projectId": "string",
      "segment": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
combinedModelId string true The ID of combined model.
isActiveCombinedModel boolean true Indicates whether this model is the active one in segmented modeling project.
modelCategory string true Indicates what kind of model this is. Will be combined for combined models.
projectId string true The ID of the project.
segmentationTaskId string true The ID of the segmentation task used to generate this combined model.
segments [SegmentProjectModelResponse] true Information for each segment. Maps each segment to the project and model used for it.

Enumerated Values

Property Value
modelCategory combined

CombinedModelSegmentsPaginatedResponse

{
  "count": 0,
  "data": [
    {
      "autopilotDone": true,
      "holdoutUnlocked": true,
      "isFrozen": true,
      "modelAssignedBy": "string",
      "modelAwardTime": "2019-08-24T14:15:22Z",
      "modelCount": 0,
      "modelIcon": [
        0
      ],
      "modelId": "string",
      "modelMetrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
      "modelType": "string",
      "projectId": "string",
      "projectPaused": true,
      "projectStage": "modeling",
      "projectStageDescription": "string",
      "projectStatusError": "string",
      "rowCount": 0,
      "rowPercentage": 0,
      "segment": "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 [CombinedModelSegmentsResponse] true List of combined model segments info.
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.

CombinedModelSegmentsResponse

{
  "autopilotDone": true,
  "holdoutUnlocked": true,
  "isFrozen": true,
  "modelAssignedBy": "string",
  "modelAwardTime": "2019-08-24T14:15:22Z",
  "modelCount": 0,
  "modelIcon": [
    0
  ],
  "modelId": "string",
  "modelMetrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelType": "string",
  "projectId": "string",
  "projectPaused": true,
  "projectStage": "modeling",
  "projectStageDescription": "string",
  "projectStatusError": "string",
  "rowCount": 0,
  "rowPercentage": 0,
  "segment": "string"
}

Properties

Name Type Required Restrictions Description
autopilotDone boolean¦null true Is autopilot done for the project.
holdoutUnlocked boolean¦null true Is holdout unlocked for the project.
isFrozen boolean¦null true Indicates whether the segment champion model is frozen, i.e. uses tuning parameters from a parent model
modelAssignedBy string¦null true Who assigned model as segment champion. Default is DataRobot.
modelAwardTime string(date-time)¦null true Time when model was awarded as segment champion.
modelCount integer¦null true Count of trained models in project.
modelIcon [integer]¦null true The number for the icon representing the given champion model.
modelId string¦null true ID of segment champion model.
modelMetrics object¦null true The performance of the model according to various metrics, where each metric has validation, crossValidation, holdout, and training scores reported, or null if they have not been computed.
modelType string¦null true The description of the model type of the given champion model.
projectId string¦null true The ID of the project.
projectPaused boolean¦null false Is project paused right now.
projectStage string¦null true The current stage of the project, where modeling indicates that the target has been successfully set and modeling and predictions may proceed.
projectStageDescription string¦null true A description of the current stage of the project.
projectStatusError string¦null false Project status error message.
rowCount integer¦null true Count of rows in project's dataset.
rowPercentage number¦null true Percentage of rows in segment project's dataset comparing to original dataset.
segment string true Segment name.

Enumerated Values

Property Value
projectStage [modeling, aim, fasteda, eda, eda2, empty]

CommonGetAndListCombinedModel

{
  "combinedModelId": "string",
  "isActiveCombinedModel": false,
  "modelCategory": "combined",
  "projectId": "string",
  "segmentationTaskId": "string"
}

Properties

Name Type Required Restrictions Description
combinedModelId string true The ID of combined model.
isActiveCombinedModel boolean true Indicates whether this model is the active one in segmented modeling project.
modelCategory string true Indicates what kind of model this is. Will be combined for combined models.
projectId string true The ID of the project.
segmentationTaskId string true The ID of the segmentation task used to generate this combined model.

Enumerated Values

Property Value
modelCategory combined

Constraints

{
  "ascii": {
    "supportsGridSearch": true
  },
  "float": {
    "max": 0,
    "min": 0,
    "supportsGridSearch": true
  },
  "floatList": {
    "maxLength": 0,
    "maxVal": 0,
    "minLength": 0,
    "minVal": 0,
    "supportsGridSearch": true
  },
  "int": {
    "max": 0,
    "min": 0,
    "supportsGridSearch": true
  },
  "intList": {
    "maxLength": 0,
    "maxVal": 0,
    "minLength": 0,
    "minVal": 0,
    "supportsGridSearch": true
  },
  "select": {
    "supportsGridSearch": true,
    "values": [
      "string"
    ]
  },
  "selectgrid": {
    "supportsGridSearch": true,
    "values": [
      "string"
    ]
  },
  "unicode": {
    "supportsGridSearch": true
  }
}

Properties

Name Type Required Restrictions Description
ascii BaseConstraintType false Indicates that the value can contain free-form ASCII text. If present, is an empty object. Note that ascii fields must be valid ASCII-encoded strings. Additionally, they may not contain semicolons or newlines.
float Float false Numeric constraints on a floating-point value. If present, indicates that this parameter's value may be a JSON number (integer or floating point).
floatList FloatList false Numeric constraints on a value of an array of floating-point numbers. If present, indicates that this parameter's value may be a JSON array of numbers (integer or floating point).
int Int false Numeric constraints on an integer value. If present, indicates that this parameter's value may be a JSON integer.
intList IntList false Numeric constraints on a value of an array of floating-point numbers. If present, indicates that this parameter's value may be a JSON array of integers.
select Select false Indicates that the value can be one selected from a list of known values.
selectgrid Select false Indicates that the value can be many selected from a list of known values.
unicode BaseConstraintType false Indicates that the value can contain free-form Unicode text. If present, is an empty object. Any valid JSON string is permitted as input. Note that DataRobot expects all Unicode JSON input to be encoded using UTF-8.

CreateRatingTableModel

{
  "ratingTableId": "string"
}

Properties

Name Type Required Restrictions Description
ratingTableId string true the rating table ID to use to create a new model

CrossValidationRetrieveResponse

{
  "cvScores": "\n        {\n            \"cvScores\": {\n                \"FVE Gamma\": {\n                    \"0.0\": 0.24334,\n                    \"1.0\": 0.17757,\n                    \"2.0\": 0.21803,\n                    \"3.0\": 0.20185,\n                    \"4.0\": 0.20576\n                },\n                \"FVE Poisson\": {\n                    \"0.0\": 0.24527,\n                    \"1.0\": 0.22092,\n                    \"2.0\": 0.22451,\n                    \"3.0\": 0.24417,\n                    \"4.0\": 0.21654\n                }\n            }\n        }\n"
}

Properties

Name Type Required Restrictions Description
cvScores object true A dictionary cvScores with sub-dictionary keyed by partition_id, each partition_id is itself a dictionary keyed by metric_name where the value is the reading for that particular metric for the partition_id.

CustomModelShortResponse

{
  "id": "string",
  "name": "string"
}

Properties

Name Type Required Restrictions Description
id string true The ID of the custom model.
name string true User-friendly name of the model.

CustomModelVersionShortResponse

{
  "id": "string",
  "label": "string"
}

Properties

Name Type Required Restrictions Description
id string true The ID of the custom model version.
label string true User-friendly name of the model version.

CustomTrainingBlueprintCreate

{
  "customModelVersionId": "string"
}

Properties

Name Type Required Restrictions Description
customModelVersionId string true The ID of the specific model version from which to create a custom training blueprint.

CustomTrainingBlueprintListResponse

{
  "count": 0,
  "data": [
    {
      "createdAt": "string",
      "customModel": {
        "id": "string",
        "name": "string"
      },
      "customModelVersion": {
        "id": "string",
        "label": "string"
      },
      "executionEnvironment": {
        "id": "string",
        "name": "string"
      },
      "executionEnvironmentVersion": {
        "id": "string",
        "label": "string"
      },
      "targetType": "Binary",
      "trainingHistory": [
        {
          "creationDate": "string",
          "lid": "string",
          "pid": "string",
          "projectModelsCount": 0,
          "projectName": "string",
          "targetName": "string"
        }
      ],
      "userBlueprintId": "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 [CustomTrainingBlueprintResponse] true List of training model blueprints.
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.

CustomTrainingBlueprintResponse

{
  "createdAt": "string",
  "customModel": {
    "id": "string",
    "name": "string"
  },
  "customModelVersion": {
    "id": "string",
    "label": "string"
  },
  "executionEnvironment": {
    "id": "string",
    "name": "string"
  },
  "executionEnvironmentVersion": {
    "id": "string",
    "label": "string"
  },
  "targetType": "Binary",
  "trainingHistory": [
    {
      "creationDate": "string",
      "lid": "string",
      "pid": "string",
      "projectModelsCount": 0,
      "projectName": "string",
      "targetName": "string"
    }
  ],
  "userBlueprintId": "string"
}

Properties

Name Type Required Restrictions Description
createdAt string true ISO-8601 timestamp of when the blueprint was created.
customModel CustomModelShortResponse true Custom model in the image.
customModelVersion CustomModelVersionShortResponse true Version of the model in the image.
executionEnvironment ExecutionEnvironmentShortResponse true Execution environment in the image.
executionEnvironmentVersion ExecutionEnvironmentVersionShortResponse true Version of the environment in the image.
targetType string true The target type of the training model.
trainingHistory [TrainingHistoryEntry] true List of instances of this blueprint having been trained.
userBlueprintId string true User Blueprint ID that can be used to train the model.

Enumerated Values

Property Value
targetType [Binary, Regression, Multiclass, Anomaly, Transform, TextGeneration, Unstructured]

DatetimeModelDetailsResponse

{
  "backtests": [
    {
      "index": 0,
      "score": 0,
      "status": "COMPLETED",
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "effectiveFeatureDerivationWindowEnd": 0,
  "effectiveFeatureDerivationWindowStart": 0,
  "featurelistId": "string",
  "featurelistName": "string",
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "hasFinetuners": true,
  "holdoutScore": 0,
  "holdoutStatus": "COMPLETED",
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"backtesting\": 0.50166,\n                    \"backtestingScores\": [0.51206, 0.49436, null, 0.62516],\n                    \"crossValidation\": null\n                },\n                \"RMSE\": {\n                    \"holdout\": null,\n                    \"validation\": 21.0836,\n                    \"backtesting\": 23.361932,\n                    \"backtestingScores\": [0.4403, 0.4213, null, 0.5132],\n                    \"crossValidation\": null\n                }\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": null,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingInfo": {
    "holdoutTrainingDuration": "string",
    "holdoutTrainingEndDate": "2019-08-24T14:15:22Z",
    "holdoutTrainingRowCount": 0,
    "holdoutTrainingStartDate": "2019-08-24T14:15:22Z",
    "predictionTrainingDuration": "string",
    "predictionTrainingEndDate": "2019-08-24T14:15:22Z",
    "predictionTrainingRowCount": 0,
    "predictionTrainingStartDate": "2019-08-24T14:15:22Z"
  },
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z",
  "windowsBasisUnit": "MILLISECOND"
}

Properties

Name Type Required Restrictions Description
backtests [BacktestStatusResponse] true information on each backtesting fold of the model
blueprintId string true The blueprint used to construct the model.
dataSelectionMethod string false Identifies which setting defines the training size of the model when making predictions and scoring. Only used by datetime models.
effectiveFeatureDerivationWindowEnd integer true maximum: 0
Only available for time series projects. How many timeUnits into the past relative to the forecast point the feature derivation window should end.
effectiveFeatureDerivationWindowStart integer true maximum: 0 (exclusive)
Only available for time series projects. How many timeUnits into the past relative to the forecast point the user needs to provide history for at prediction time. This can differ from the featureDerivationWindowStart set on the project due to the differencing method and period selected.
featurelistId string¦null true the ID of the featurelist used by the model
featurelistName string¦null true the name of the featurelist used by the model.If null, the model was trained on multiple feature lists.
forecastWindowEnd integer true minimum: 0
Only available for time series projects. How many timeUnits into the future relative to the forecast point the forecast window should end.
forecastWindowStart integer true minimum: 0
Only available for time series projects. How many timeUnits into the future relative to the forecast point the forecast window should start.
hasFinetuners boolean false Whether a model has fine tuners.
holdoutScore number¦null true the holdout score of the model according to the project metric, if the score is available and the holdout is unlocked
holdoutStatus string true the status of the holdout fold
id string true the ID of the model
isAugmented boolean false Whether a model was trained using augmentation.
isFrozen boolean true Indicates whether the model is frozen, i.e., uses tuning parameters from a parent model.
isNClustersDynamicallyDetermined boolean false Whether number of clusters is dynamically determined. Only valid in unsupervised clustering projects.
isStarred boolean true whether the model has been starred
isTrainedIntoHoldout boolean true Indicates if model used holdout data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or whenthe model's training row count was greater than the max allowed validation size.
isTrainedIntoValidation boolean true Indicates if model used validation data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or when the model's training row count was greater than the max allowed training size.
lifecycle ModelLifecycle true Object returning model lifecycle.
linkFunction string¦null true The link function the final modeler uses in the blueprint. If no link function exists, returns null.
metrics object true Object where each metric has validation, backtesting, backtestingScores and holdout scores reported, or null if they have not been computed. The validation score will be the score of the first backtest, which will be computed during initial model training. The backtesting and backtestingScores scores are computed when requested via POST /api/v2/projects/{projectId}/datetimeModels/{modelId}/backtests/. The backtesting score is the average score across all backtests. The backtestingScores is an array of scores for each backtest, with the scores reported as null if the backtest score is unavailable. The holdout score is the score against the holdout data, using the training data defined in trainingInfo.
modelCategory string true Indicates the kind of model. Returns prime for DataRobot Prime models, blend for blender models, combined for combined models, and model for all other models.
modelFamily string true the family model belongs to, e.g. SVM, GBM, etc.
modelFamilyFullName string true The full name of the family that the model belongs to. For e.g., Support Vector Machine, Gradient Boosting Machine, etc.
modelNumber integer¦null true minimum: 0 (exclusive)
The model number from the leaderboard.
modelType string true identifies the model, e.g. Nystroem Kernel SVM Regressor
monotonicDecreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
monotonicIncreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
nClusters integer¦null false The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
parentModelId string¦null true The ID of the parent model if the model is frozen or a result of incremental learning. Null otherwise.
predictionThreshold number true maximum: 1
minimum: 0
threshold used for binary classification in predictions.
predictionThresholdReadOnly boolean true indicates whether modification of a predictions threshold is forbidden. Since v2.22 threshold modification is allowed.
processes [string]¦null true list of processes used by the model
projectId string true the ID of the project to which the model belongs
samplePct string true always null for datetime models
samplingMethod string false indicates sampling method used to select training data in datetime models. For row-based project this is the way how requested number of rows are selected.For other projects (duration-based, start/end, project settings) - how specified percent of rows (timeWindowSamplePct) is selected from specified time window.
supportsComposableMl boolean true indicates whether this model is supported in Composable ML.
supportsMonotonicConstraints boolean true whether this model supports enforcing monotonic constraints
timeWindowSamplePct integer¦null false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99, indicating the percentage of sampling within the time window. The points kept are determined by samplingMethod option. Will be null if no sampling was specified. Only used by datetime models.
trainingDuration string¦null true the duration spanned by the dates in the partition column for the data used to train the model
trainingEndDate string(date-time)¦null true the end date of the dates in the partition column for the data used to train the model
trainingInfo TrainingInfoResponse true holdout and prediction training data details
trainingRowCount integer¦null true minimum: 0 (exclusive)
The number of rows used to train the model.
trainingStartDate string(date-time)¦null true the start date of the dates in the partition column for the data used to train the model
windowsBasisUnit string true Only available for time series projects. Indicates which unit is the basis for the feature derivation window and the forecast window.

Enumerated Values

Property Value
dataSelectionMethod [duration, rowCount, selectedDateRange, useProjectSettings]
holdoutStatus [COMPLETED, INSUFFICIENT_DATA, HOLDOUT_BOUNDARIES_EXCEEDED]
modelCategory [model, prime, blend, combined, incrementalLearning]
samplePct null
samplingMethod [random, latest]
windowsBasisUnit [MILLISECOND, SECOND, MINUTE, HOUR, DAY, WEEK, MONTH, QUARTER, YEAR, ROW]

DatetimeModelSubmissionResponse

{
  "message": "string"
}

Properties

Name Type Required Restrictions Description
message string true 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 was created.

DatetimeModelsResponse

{
  "count": 0,
  "data": [
    {
      "backtests": [
        {
          "index": 0,
          "score": 0,
          "status": "COMPLETED",
          "trainingDuration": "string",
          "trainingEndDate": "2019-08-24T14:15:22Z",
          "trainingRowCount": 0,
          "trainingStartDate": "2019-08-24T14:15:22Z"
        }
      ],
      "blueprintId": "string",
      "dataSelectionMethod": "duration",
      "effectiveFeatureDerivationWindowEnd": 0,
      "effectiveFeatureDerivationWindowStart": 0,
      "featurelistId": "string",
      "featurelistName": "string",
      "forecastWindowEnd": 0,
      "forecastWindowStart": 0,
      "hasFinetuners": true,
      "holdoutScore": 0,
      "holdoutStatus": "COMPLETED",
      "id": "string",
      "isAugmented": true,
      "isFrozen": true,
      "isNClustersDynamicallyDetermined": true,
      "isStarred": true,
      "isTrainedIntoHoldout": true,
      "isTrainedIntoValidation": true,
      "lifecycle": {
        "reason": "string",
        "stage": "active"
      },
      "linkFunction": "string",
      "metrics": "\n        {\n            \"metrics\": {\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"backtesting\": 0.50166,\n                    \"backtestingScores\": [0.51206, 0.49436, null, 0.62516],\n                    \"crossValidation\": null\n                },\n                \"RMSE\": {\n                    \"holdout\": null,\n                    \"validation\": 21.0836,\n                    \"backtesting\": 23.361932,\n                    \"backtestingScores\": [0.4403, 0.4213, null, 0.5132],\n                    \"crossValidation\": null\n                }\n            }\n        }\n",
      "modelCategory": "model",
      "modelFamily": "string",
      "modelFamilyFullName": "string",
      "modelNumber": 0,
      "modelType": "string",
      "monotonicDecreasingFeaturelistId": "string",
      "monotonicIncreasingFeaturelistId": "string",
      "nClusters": 0,
      "parentModelId": "string",
      "predictionThreshold": 1,
      "predictionThresholdReadOnly": true,
      "processes": [
        "string"
      ],
      "projectId": "string",
      "samplePct": null,
      "samplingMethod": "random",
      "supportsComposableMl": true,
      "supportsMonotonicConstraints": true,
      "timeWindowSamplePct": 0,
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingInfo": {
        "holdoutTrainingDuration": "string",
        "holdoutTrainingEndDate": "2019-08-24T14:15:22Z",
        "holdoutTrainingRowCount": 0,
        "holdoutTrainingStartDate": "2019-08-24T14:15:22Z",
        "predictionTrainingDuration": "string",
        "predictionTrainingEndDate": "2019-08-24T14:15:22Z",
        "predictionTrainingRowCount": 0,
        "predictionTrainingStartDate": "2019-08-24T14:15:22Z"
      },
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z",
      "windowsBasisUnit": "MILLISECOND"
    }
  ],
  "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 [DatetimeModelDetailsResponse] true each has the same schema as if retrieving the model individually from GET /api/v2/projects/{projectId}/datetimeModels/{modelId}/.
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).

DependencyBuildLogResponse

{
  "data": "string"
}

Properties

Name Type Required Restrictions Description
data string(binary) true The custom model version's dependency build log in tar.gz format.

DeploymentPredictionEnvironmentResponse

{
  "id": "string",
  "isManagedByManagementAgent": true,
  "name": "string",
  "platform": "aws",
  "plugin": "string",
  "supportedModelFormats": [
    "datarobot"
  ]
}

Properties

Name Type Required Restrictions Description
id string¦null true ID of the PredictionEnvironment.
isManagedByManagementAgent boolean true True if PredictionEnvironment is using Management Agent.
name string true Name of the PredictionEnvironment.
platform string true Platform of the PredictionEnvironment.
plugin string¦null false Plugin name of the PredictionEnvironment.
supportedModelFormats [string] false maxItems: 4
minItems: 1
Model formats that the PredictionEnvironment supports.

Enumerated Values

Property Value
platform [aws, gcp, azure, onPremise, datarobot, openShift, other, snowflake]

DerivedFeatures

{
  "coefficient": 0,
  "derivedFeature": "string",
  "originalFeature": "string",
  "stageCoefficients": [
    {
      "coefficient": 0,
      "stage": "string"
    }
  ],
  "transformations": [
    {
      "name": "string",
      "value": "string"
    }
  ],
  "type": "string"
}

Properties

Name Type Required Restrictions Description
coefficient number true The coefficient for this feature.
derivedFeature string true The name of the derived feature.
originalFeature string true The name of the feature used to derive this feature.
stageCoefficients [StageCoefficients] true An array of json objects describing separate coefficients for every stage of model (empty for single stage models).
transformations [Transformations] true An array of json objects describing the transformations applied to create this derived feature.
type string true The type of this feature.

Empty

{}

Properties

None

EureqaDistributionDetailResponse

{
  "bins": [
    {
      "binEnd": 0,
      "binStart": 0,
      "negatives": 0,
      "positives": 0
    }
  ],
  "complexity": 0,
  "error": 0,
  "errorMetric": "string",
  "eureqaSolutionId": "string",
  "expression": "string",
  "expressionAnnotated": "string",
  "threshold": 0
}

Properties

Name Type Required Restrictions Description
bins [ClassificationBinDataResponse] true The distribution plot data.
complexity integer true The complexity score for this solution. Complexity score is a function of the mathematical operators used in the current solution. The complexity calculation can be tuned via model hyperparameters.
error number¦null true The error for the current solution, as computed by eureqa using the errorMetric error metric. None if Eureqa model refitted existing solutions.
errorMetric string true The Eureqa error metric identifier used to compute error metrics for this search. Note that Eureqa error metrics do not correspond 1:1 with DataRobot error metrics - the available metrics are not the same, and even equivalent metrics may be computed slightly differently.
eureqaSolutionId string true The ID of the solution.
expression string true The eureqa "solution string". This is a mathematical expression; human-readable but with strict syntax specifications defined by Eureqa.
expressionAnnotated string true The expression, rendered with additional tags to assist in automatic parsing.
threshold number true Classifier threshold selected by the backend, used to determine which model values are binned as positive and which are binned as negative. Must have a value between the binStart of the first bin and binEnd of the last bin.

EureqaLeaderboardEntryPayload

{
  "parentModelId": "string",
  "solutionId": "string"
}

Properties

Name Type Required Restrictions Description
parentModelId string false The ID of the model to clone from. If omitted, will automatically search for and find the first leaderboard model created by the blueprint run that also created the solution associated with solutionId.
solutionId string true the ID of the solution to be cloned.

EureqaModelDetailResponse

{
  "complexity": 0,
  "error": 0,
  "errorMetric": "string",
  "eureqaSolutionId": "string",
  "expression": "string",
  "expressionAnnotated": "string",
  "plotData": [
    {
      "actual": 0,
      "predicted": 0,
      "row": 0
    }
  ]
}

Properties

Name Type Required Restrictions Description
complexity integer true The complexity score for this solution. Complexity score is a function of the mathematical operators used in the current solution. The complexity calculation can be tuned via model hyperparameters.
error number¦null true The error for the current solution, as computed by eureqa using the errorMetric error metric. None if Eureqa model refitted existing solutions.
errorMetric string true The Eureqa error metric identifier used to compute error metrics for this search. Note that Eureqa error metrics do not correspond 1:1 with DataRobot error metrics - the available metrics are not the same, and even equivalent metrics may be computed slightly differently.
eureqaSolutionId string true The ID of the solution.
expression string true The eureqa "solution string". This is a mathematical expression; human-readable but with strict syntax specifications defined by Eureqa.
expressionAnnotated string true The expression, rendered with additional tags to assist in automatic parsing.
plotData [PlotDataResponse] true The plot data.

ExecutionEnvironmentShortResponse

{
  "id": "string",
  "name": "string"
}

Properties

Name Type Required Restrictions Description
id string true The ID of the execution environment.
name string true User-friendly name of the execution environment.

ExecutionEnvironmentVersionShortResponse

{
  "id": "string",
  "label": "string"
}

Properties

Name Type Required Restrictions Description
id string true The ID of the execution environment version.
label string true User-friendly name of the execution environment version.

Feature

{
  "dateFormat": "string",
  "featureType": "string",
  "importance": 0,
  "knownInAdvance": true,
  "name": "string"
}

Properties

Name Type Required Restrictions Description
dateFormat string¦null true The date format string for how this feature was interpreted.
featureType string¦null true Feature type.
importance number¦null true Numeric measure of the relationship strength between the feature and target (independent of model or other features).
knownInAdvance boolean true Whether the feature was selected as known in advance in a time-series model, false for non-time-series models.
name string true Feature name.

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.

FeatureImpactCreateResponse

{
  "statusId": "string"
}

Properties

Name Type Required Restrictions Description
statusId string true ID that can be used with GET /api/v2/status/{statusId}/ for tracking job status.

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.

FeatureImpactResponse

{
  "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
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/

FeatureListResponse

{
  "count": 0,
  "data": [
    {
      "dateFormat": "string",
      "featureType": "string",
      "importance": 0,
      "knownInAdvance": true,
      "name": "string"
    }
  ],
  "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 [Feature] true An array of dataset details.
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).

Float

{
  "max": 0,
  "min": 0,
  "supportsGridSearch": true
}

Properties

Name Type Required Restrictions Description
max number true Maximum value for the parameter.
min number true Minimum value for the parameter.
supportsGridSearch boolean true When True, Grid Search is supported for this parameter.

FloatList

{
  "maxLength": 0,
  "maxVal": 0,
  "minLength": 0,
  "minVal": 0,
  "supportsGridSearch": true
}

Properties

Name Type Required Restrictions Description
maxLength integer true minimum: 0
Maximum permitted length of the list.
maxVal number true Maximum permitted value.
minLength integer true minimum: 0
Minimum permitted length of the list.
minVal number true Minimum permitted value.
supportsGridSearch boolean true When True, Grid Search is supported for this parameter.

FrozenModelCreate

{
  "modelId": "string",
  "nClusters": 2,
  "samplePct": 0,
  "trainingRowCount": 0
}

Properties

Name Type Required Restrictions Description
modelId string true the ID of an existing model to use as a source of training parameters.
nClusters integer false maximum: 100
minimum: 2
The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
samplePct number false the percentage of the dataset to use with the model. Only one of samplePct and trainingRowCount should be specified. The specified percentage should be between 0.0 and 100.0.
trainingRowCount integer false the integer number of rows of the dataset to use with the model. Only one of samplePct and trainingRowCount should be specified.

FrozenModelListResponse

{
  "count": 0,
  "data": [
    {
      "blueprintId": "string",
      "dataSelectionMethod": "duration",
      "featurelistId": "string",
      "featurelistName": "string",
      "hasFinetuners": true,
      "id": "string",
      "isAugmented": true,
      "isFrozen": true,
      "isNClustersDynamicallyDetermined": true,
      "isStarred": true,
      "isTrainedIntoHoldout": true,
      "isTrainedIntoValidation": true,
      "lifecycle": {
        "reason": "string",
        "stage": "active"
      },
      "linkFunction": "string",
      "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
      "modelCategory": "model",
      "modelFamily": "string",
      "modelFamilyFullName": "string",
      "modelNumber": 0,
      "modelType": "string",
      "monotonicDecreasingFeaturelistId": "string",
      "monotonicIncreasingFeaturelistId": "string",
      "nClusters": 0,
      "parentModelId": "string",
      "predictionThreshold": 1,
      "predictionThresholdReadOnly": true,
      "processes": [
        "string"
      ],
      "projectId": "string",
      "samplePct": 0,
      "samplingMethod": "random",
      "supportsComposableMl": true,
      "supportsMonotonicConstraints": true,
      "timeWindowSamplePct": 0,
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "next": "string",
  "previous": "string",
  "totalCount": 0
}

Properties

Name Type Required Restrictions Description
count integer true Number of items returned on this page.
data [ModelDetailsResponse] true An array of the frozen models in a project.
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)
totalCount integer false Total number of records.

GrantAccessControlWithId

{
  "id": "string",
  "role": "string",
  "shareRecipientType": "user"
}

Properties

Name Type Required Restrictions Description
id string true The ID of the recipient.
role string true The role of the recipient on this entity. One of OWNER, USER, OBSERVER.
shareRecipientType string true Describes the recipient type, either user, group, or organization.

Enumerated Values

Property Value
shareRecipientType [user, group, organization]

GrantAccessControlWithUsername

{
  "role": "string",
  "shareRecipientType": "user",
  "username": "string"
}

Properties

Name Type Required Restrictions Description
role string true The role of the recipient on this entity. One of OWNER, USER, OBSERVER.
shareRecipientType string true Describes the recipient type, either user, group, or organization.
username string true Username of the user to update the access role for.

Enumerated Values

Property Value
shareRecipientType [user, group, organization]

HyperparametersResponse

{
  "buildingBlocks": {},
  "errorMetric": "string",
  "maxGenerations": 32,
  "numThreads": 0,
  "priorSolutions": [
    "string"
  ],
  "randomSeed": 0,
  "splitMode": "custom",
  "syncMigrations": true,
  "targetExpressionFormat": "None",
  "targetExpressionString": "string",
  "timeoutSec": 0,
  "trainingFraction": 1,
  "trainingSplitExpr": "string",
  "validationFraction": 1,
  "validationSplitExpr": "string",
  "weightExpr": "string"
}

Properties

Name Type Required Restrictions Description
buildingBlocks object¦null true Mathematical operators and other components that comprise Eureqa Expressions.
errorMetric string¦null false Error Metric Eureqa used internally, to evaluate which models to keep on its internal Pareto Front.
maxGenerations integer¦null true minimum: 32
The maximum number of evolutionary generations to run.
numThreads integer¦null true minimum: 0
The number of threads Eureqa will run with.
priorSolutions [string]¦null true Prior Eureqa Solutions.
randomSeed integer¦null true minimum: 0
Constant to seed Eureqa's pseudo-random number generator.
splitMode string¦null true Whether to perform in-order (2) or random (1) splitting within the training set, for evolutionary re-training and re-validatoon.
syncMigrations boolean¦null true Whether Eureqa's migrations are synchronized.
targetExpressionFormat string¦null true Constrain the target expression to the specified format.
targetExpressionString string¦null true Eureqa Expression to constrain the form of the models that Eureqa will consider.
timeoutSec number¦null true minimum: 0
The duration of time to run the Eureqa search algorithm for Eureqa will run until either of max_generations or timeout_sec is reached.
trainingFraction number¦null true maximum: 1
minimum: 0
The fraction of the DataRobot training data to use for Eureqa evolutionary training.
trainingSplitExpr string¦null true Valid Eureqa Expression to do Eureqa internal training splits.
validationFraction number¦null true maximum: 1
minimum: 0
The fraction of the DataRobot training data to use for Eureqa evolutionary validation.
validationSplitExpr string¦null true Valid Eureqa Expression to do Eureqa internal validation splits.
weightExpr string¦null true Eureqa Weight Expression.

Enumerated Values

Property Value
splitMode [custom, 1, 2]
targetExpressionFormat [None, exponential, featureInteraction]

Int

{
  "max": 0,
  "min": 0,
  "supportsGridSearch": true
}

Properties

Name Type Required Restrictions Description
max integer true Maximum value for the parameter.
min integer true Minimum value for the parameter.
supportsGridSearch boolean true When True, Grid Search is supported for this parameter.

IntList

{
  "maxLength": 0,
  "maxVal": 0,
  "minLength": 0,
  "minVal": 0,
  "supportsGridSearch": true
}

Properties

Name Type Required Restrictions Description
maxLength integer true minimum: 0
Maximum permitted length of the list.
maxVal integer true Maximum permitted value.
minLength integer true minimum: 0
Minimum permitted length of the list.
minVal integer true Minimum permitted value.
supportsGridSearch boolean true When True, Grid Search is supported for this parameter.

MessagesInfo

{
  "messages": [
    {
      "additionalInfo": [
        "string"
      ],
      "messageLevel": "CRITICAL",
      "messageText": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
messages [OneMessageInfo] true maxItems: 50
minItems: 1
List of data quality messages. The list may include reports on more than one data quality issue, if present.

MissingReportRetrieve

{
  "missingValuesReport": [
    {
      "feature": "string",
      "missingCount": 0,
      "missingPercentage": 1,
      "tasks": {
        "property1": {
          "descriptions": [
            "string"
          ],
          "name": "string"
        },
        "property2": {
          "descriptions": [
            "string"
          ],
          "name": "string"
        }
      },
      "type": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
missingValuesReport [PerFeatureMissingReport] true Missing values report, which contains an array of reports for individual features

MlpkgFileContents

{
  "allTimeSeriesPredictionIntervals": true
}

Properties

Name Type Required Restrictions Description
allTimeSeriesPredictionIntervals boolean¦null false Whether .mlpkg contains TS prediction intervals computed for all percentiles

ModelAdvancedTuning

{
  "tuningDescription": "string",
  "tuningParameters": [
    {
      "parameterId": "string",
      "value": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
tuningDescription string false Human-readable description of this advanced-tuning request.
tuningParameters [TuningParameter] true Parameters to tune.

ModelCapabilitiesRetrieveResponse

{
  "eligibleForPrime": true,
  "hasParameters": true,
  "hasWordCloud": true,
  "reasons": {
    "supportsDocumentTextExtractionSampleInsight": "string",
    "supportsImageActivationMaps": "string",
    "supportsImageEmbedding": "string",
    "supportsLiftChart": "string",
    "supportsResiduals": "string",
    "supportsRocCurve": "string"
  },
  "supportsBlending": true,
  "supportsCodeGeneration": true,
  "supportsCoefficients": true,
  "supportsDocumentTextExtractionSampleInsight": true,
  "supportsEarlyStopping": true,
  "supportsImageActivationMaps": true,
  "supportsImageEmbedding": true,
  "supportsLiftChart": true,
  "supportsModelPackageExport": true,
  "supportsModelTrainingMetrics": true,
  "supportsMonotonicConstraints": true,
  "supportsNNVisualizations": true,
  "supportsResiduals": true,
  "supportsRocCurve": true,
  "supportsShap": true
}

Properties

Name Type Required Restrictions Description
eligibleForPrime boolean true True if the model is eligible for prime. Use GET /api/v2/projects/{projectId}/models/{modelId}/primeInfo/ to request additional details if the model is not eligible.
hasParameters boolean true True if the model has parameters that can be retrieved. Use GET /api/v2/projects/{projectId}/models/{modelId}/parameters/ to retrieve the model parameters.
hasWordCloud boolean true True` if the model has word cloud data available. Use GET /api/v2/projects/{projectId}/models/{modelId}/wordCloud/ to retrieve a word cloud.
reasons Reasons false Information on why capability is unsupported for the model.
supportsBlending boolean true True if the model supports blending. See POST /api/v2/projects/{projectId}/blenderModels/blendCheck/ to check specific blending combinations.
supportsCodeGeneration boolean true True if the model supports export of model's source code or compiled Java executable.
supportsCoefficients boolean true True if model coefficients are available.
supportsDocumentTextExtractionSampleInsight boolean true True if the model has document column(s) and document text extraction samples can be generated.
supportsEarlyStopping boolean false True if this is an early stopping tree-based model and number of trained iterations can be retrieved.
supportsImageActivationMaps boolean true True if the model has image column(s) and activation maps can be generated.
supportsImageEmbedding boolean true True if the model has image column(s) and image embeddings can be generated.
supportsLiftChart boolean true True if Lift Chart can be generated.
supportsModelPackageExport boolean false True if the model can be exported as a model package.
supportsModelTrainingMetrics boolean true When True , the model will track and save key training metrics in an effort to communicate model accuracy throughout training, rather than at training completion.
supportsMonotonicConstraints boolean true True if the model supports monotonic constraints.
supportsNNVisualizations boolean true True if the model supports neuralNetworkVisualizations.
supportsResiduals boolean true When True, the model supports residuals and residuals data can be retrieved.
supportsRocCurve boolean true True if ROC Curve can be generated.
supportsShap boolean true True if the model supports Shapley package. i.e. Shapley based feature Importance

ModelDetailsResponse

{
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": 0,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Properties

Name Type Required Restrictions Description
blueprintId string true The blueprint used to construct the model.
dataSelectionMethod string false Identifies which setting defines the training size of the model when making predictions and scoring. Only used by datetime models.
featurelistId string¦null true the ID of the featurelist used by the model
featurelistName string¦null true the name of the featurelist used by the model.If null, the model was trained on multiple feature lists.
hasFinetuners boolean false Whether a model has fine tuners.
id string true the ID of the model
isAugmented boolean false Whether a model was trained using augmentation.
isFrozen boolean true Indicates whether the model is frozen, i.e., uses tuning parameters from a parent model.
isNClustersDynamicallyDetermined boolean false Whether number of clusters is dynamically determined. Only valid in unsupervised clustering projects.
isStarred boolean true whether the model has been starred
isTrainedIntoHoldout boolean true Indicates if model used holdout data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or whenthe model's training row count was greater than the max allowed validation size.
isTrainedIntoValidation boolean true Indicates if model used validation data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or when the model's training row count was greater than the max allowed training size.
lifecycle ModelLifecycle true Object returning model lifecycle.
linkFunction string¦null true The link function the final modeler uses in the blueprint. If no link function exists, returns null.
metrics object true the performance of the model according to various metrics, where each metric has validation, crossValidation, holdout, and training scores reported, or null if they have not been computed.
modelCategory string true Indicates the kind of model. Returns prime for DataRobot Prime models, blend for blender models, combined for combined models, and model for all other models.
modelFamily string true the family model belongs to, e.g. SVM, GBM, etc.
modelFamilyFullName string true The full name of the family that the model belongs to. For e.g., Support Vector Machine, Gradient Boosting Machine, etc.
modelNumber integer¦null true minimum: 0 (exclusive)
The model number from the leaderboard.
modelType string true identifies the model, e.g. Nystroem Kernel SVM Regressor
monotonicDecreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
monotonicIncreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
nClusters integer¦null false The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
parentModelId string¦null true The ID of the parent model if the model is frozen or a result of incremental learning. Null otherwise.
predictionThreshold number true maximum: 1
minimum: 0
threshold used for binary classification in predictions.
predictionThresholdReadOnly boolean true indicates whether modification of a predictions threshold is forbidden. Since v2.22 threshold modification is allowed.
processes [string]¦null true list of processes used by the model
projectId string true the ID of the project to which the model belongs
samplePct number¦null true minimum: 0 (exclusive)
the percentage of the dataset used in training the model
samplingMethod string false indicates sampling method used to select training data in datetime models. For row-based project this is the way how requested number of rows are selected.For other projects (duration-based, start/end, project settings) - how specified percent of rows (timeWindowSamplePct) is selected from specified time window.
supportsComposableMl boolean true indicates whether this model is supported in Composable ML.
supportsMonotonicConstraints boolean true whether this model supports enforcing monotonic constraints
timeWindowSamplePct integer¦null false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99, indicating the percentage of sampling within the time window. The points kept are determined by samplingMethod option. Will be null if no sampling was specified. Only used by datetime models.
trainingDuration string¦null true the duration spanned by the dates in the partition column for the data used to train the model
trainingEndDate string(date-time)¦null true the end date of the dates in the partition column for the data used to train the model
trainingRowCount integer¦null true minimum: 0 (exclusive)
The number of rows used to train the model.
trainingStartDate string(date-time)¦null true the start date of the dates in the partition column for the data used to train the model

Enumerated Values

Property Value
dataSelectionMethod [duration, rowCount, selectedDateRange, useProjectSettings]
modelCategory [model, prime, blend, combined, incrementalLearning]
samplingMethod [random, latest]

ModelFeatureListResponse

{
  "aPrioriFeatureNames": [
    "string"
  ],
  "featureNames": [
    "string"
  ],
  "knownInAdvanceFeatureNames": [
    "string"
  ]
}

Properties

Name Type Required Restrictions Description
aPrioriFeatureNames [string] true (Deprecated in version v2.11) Renamed to knownInAdvanceFeatureNames. This parameter always has the same value as knownInAdvanceFeatureNames and will be removed in a future release.
featureNames [string] true An array of the names of all features used by the specified model.
knownInAdvanceFeatureNames [string] true An array of the names of time series known-in-advance features used by the specified model.

ModelJobResponse

{
  "blueprintId": "string",
  "featurelistId": "string",
  "id": "string",
  "isBlocked": true,
  "isTrainedOnGpu": true,
  "modelCategory": "model",
  "modelId": "string",
  "modelType": "string",
  "processes": [
    "string"
  ],
  "projectId": "string",
  "samplePct": 0,
  "status": "queue"
}

Properties

Name Type Required Restrictions Description
blueprintId string true The blueprint used by the model - note that this is not an ObjectId.
featurelistId string true The ID of the featurelist the model is using.
id string true The job ID.
isBlocked boolean true True if a job is waiting for its dependencies to be resolved first.
isTrainedOnGpu boolean false True if the job was trained using GPU capabilities
modelCategory string true Indicates what kind of model this is. Will be combined for combined models.
modelId string true The ID of the model
modelType string true The type of model used by the job.
processes [string] true List of processes the modeling job includes
projectId string true The project the job belongs to.
samplePct number false The percentage of the dataset the job is using.
status string true The status of the job.

Enumerated Values

Property Value
modelCategory [model, prime, blend]
status [queue, inprogress, error, ABORTED, COMPLETED]

ModelLifecycle

{
  "reason": "string",
  "stage": "active"
}

Properties

Name Type Required Restrictions Description
reason string¦null true Reason for lifecycle stage. None if model is active.
stage string true Model lifecycle stage.

Enumerated Values

Property Value
stage [active, deprecated, disabled]

ModelPackageCapabilities

{
  "supportsAutomaticActuals": true,
  "supportsChallengerModels": true,
  "supportsFeatureDriftTracking": true,
  "supportsHumilityRecommendedRules": true,
  "supportsHumilityRules": true,
  "supportsHumilityRulesDefaultCalculations": true,
  "supportsPredictionWarning": true,
  "supportsRetraining": true,
  "supportsScoringCodeDownload": true,
  "supportsSecondaryDatasets": true,
  "supportsSegmentedAnalysisDriftAndAccuracy": true,
  "supportsShapBasedPredictionExplanations": true,
  "supportsTargetDriftTracking": true
}

Properties

Name Type Required Restrictions Description
supportsAutomaticActuals boolean false Whether inferring actual values from time series history data and automatically feeding them back for accuracy estimation is supported by this model package.
supportsChallengerModels boolean true Whether Challenger Models are supported by this model package.
supportsFeatureDriftTracking boolean true Whether Feature Drift is supported by this model package.
supportsHumilityRecommendedRules boolean true Whether calculating values for recommended Humility Rules is supported by this model package.
supportsHumilityRules boolean true Whether Humility Rules are supported by this model package.
supportsHumilityRulesDefaultCalculations boolean true Whether calculating default values for Humility Rules is supported by this model package.
supportsPredictionWarning boolean true Whether Prediction Warnings are supported by this model package.
supportsRetraining boolean false Whether deployment supports retraining.
supportsScoringCodeDownload boolean false Whether scoring code download is supported by this model package.
supportsSecondaryDatasets boolean true If the deployments supports secondary datasets.
supportsSegmentedAnalysisDriftAndAccuracy boolean true Whether tracking features in training and predictions data for segmented analysis is supported by this model package.
supportsShapBasedPredictionExplanations boolean true Whether shap-based prediction explanations are supported by this model package.
supportsTargetDriftTracking boolean true Whether Target Drift is supported by this model package.

ModelPackageCapabilitiesRetrieveResponse

{
  "data": [
    {
      "messages": [
        "string"
      ],
      "name": "string",
      "supported": true
    }
  ]
}

Properties

Name Type Required Restrictions Description
data [ModelPackageCapability] true List of all capabilities.

ModelPackageCapability

{
  "messages": [
    "string"
  ],
  "name": "string",
  "supported": true
}

Properties

Name Type Required Restrictions Description
messages [string] true Messages explaining why the capability is supported or not supported.
name string true The name of the capability.
supported boolean true If the capability is supported.

ModelPackageCreateFromLeaderboard

{
  "computeAllTsIntervals": null,
  "description": "",
  "distributionPredictionModelId": null,
  "modelId": "string",
  "name": null,
  "predictionThreshold": 1
}

Properties

Name Type Required Restrictions Description
computeAllTsIntervals boolean¦null false Whether to compute all Time Series prediction intervals (1-100 percentiles)
description string¦null false maxLength: 2048
Description of the model package.
distributionPredictionModelId string¦null false ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
modelId string true ID of the DataRobot model.
name string¦null false maxLength: 512
Name of the model package.
predictionThreshold number false maximum: 1
minimum: 0
Threshold used for binary classification in predictions

ModelPackageCreateFromLearningModel

{
  "description": "string",
  "distributionPredictionModelId": null,
  "modelId": "string",
  "name": null,
  "predictionThreshold": 1
}

Properties

Name Type Required Restrictions Description
description string¦null false maxLength: 2048
Description of the model package.
distributionPredictionModelId string¦null false ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
modelId string true ID of the DataRobot model.
name string¦null false maxLength: 512
Name of the model package.
predictionThreshold number false maximum: 1
minimum: 0
Threshold used for binary classification in predictions

ModelPackageDatasets

{
  "baselineSegmentedBy": [
    "string"
  ],
  "datasetName": "string",
  "holdoutDataCatalogId": "string",
  "holdoutDataCatalogVersionId": "string",
  "holdoutDatasetName": "string",
  "targetHistogramBaseline": "predictions",
  "trainingDataCatalogId": "string",
  "trainingDataCatalogVersionId": "string",
  "trainingDataSize": 0
}

Properties

Name Type Required Restrictions Description
baselineSegmentedBy [string]¦null true Names of categorical features by which the training baseline was segmented. This allows for deployment prediction requests to be segmented by those same features. Segmenting the training baseline by these features allows for users to perform segmented analysis of Data Drift and Accuracy, and to compare the same subset of training and scoring data based on the selected segment attribute and segment value.
datasetName string¦null true Name of dataset used to train the model
holdoutDataCatalogId string¦null true ID for holdout data (returned from uploading a data set)
holdoutDataCatalogVersionId string¦null true Version ID for holdout data (returned from uploading a data set)
holdoutDatasetName string¦null true Name of dataset used for model holdout
targetHistogramBaseline string false Values used to establish the training baseline
trainingDataCatalogId string¦null true ID for training data (returned from uploading a data set)
trainingDataCatalogVersionId string¦null true Version ID for training data (returned from uploading a data set)
trainingDataSize integer false Number of rows in training data (used by DR models)

Enumerated Values

Property Value
targetHistogramBaseline [predictions, actuals]

ModelPackageImportMeta

{
  "containsFearPipeline": true,
  "containsFeaturelists": true,
  "containsLeaderboardMeta": true,
  "containsProjectMeta": true,
  "creatorFullName": "string",
  "creatorId": "string",
  "creatorUsername": "string",
  "dateCreated": "string",
  "originalFileName": "string"
}

Properties

Name Type Required Restrictions Description
containsFearPipeline boolean¦null false Exists for imported models only, indicates thatmodel package contains file with fear pipeline.
containsFeaturelists boolean¦null false Exists for imported models only, indicates thatmodel package contains file with featurelists.
containsLeaderboardMeta boolean¦null false Exists for imported models only, indicates thatmodel package contains file with leaderboard meta.
containsProjectMeta boolean¦null false Exists for imported models only, indicates thatmodel package contains file with project meta.
creatorFullName string¦null true Full name of the person who created this model package
creatorId string true User ID of the person who created this Model Package
creatorUsername string true Username of the person who created this model package
dateCreated string true When this Model Package was created
originalFileName string¦null true Exists for imported models only, the original file name that was uploaded

ModelPackageListResponse

{
  "count": 0,
  "data": [
    {
      "activeDeploymentCount": 0,
      "buildStatus": "inProgress",
      "capabilities": {
        "supportsAutomaticActuals": true,
        "supportsChallengerModels": true,
        "supportsFeatureDriftTracking": true,
        "supportsHumilityRecommendedRules": true,
        "supportsHumilityRules": true,
        "supportsHumilityRulesDefaultCalculations": true,
        "supportsPredictionWarning": true,
        "supportsRetraining": true,
        "supportsScoringCodeDownload": true,
        "supportsSecondaryDatasets": true,
        "supportsSegmentedAnalysisDriftAndAccuracy": true,
        "supportsShapBasedPredictionExplanations": true,
        "supportsTargetDriftTracking": true
      },
      "datasets": {
        "baselineSegmentedBy": [
          "string"
        ],
        "datasetName": "string",
        "holdoutDataCatalogId": "string",
        "holdoutDataCatalogVersionId": "string",
        "holdoutDatasetName": "string",
        "targetHistogramBaseline": "predictions",
        "trainingDataCatalogId": "string",
        "trainingDataCatalogVersionId": "string",
        "trainingDataSize": 0
      },
      "id": "string",
      "importMeta": {
        "containsFearPipeline": true,
        "containsFeaturelists": true,
        "containsLeaderboardMeta": true,
        "containsProjectMeta": true,
        "creatorFullName": "string",
        "creatorId": "string",
        "creatorUsername": "string",
        "dateCreated": "string",
        "originalFileName": "string"
      },
      "isArchived": true,
      "isDeprecated": true,
      "mlpkgFileContents": {
        "allTimeSeriesPredictionIntervals": true
      },
      "modelDescription": {
        "buildEnvironmentType": "DataRobot",
        "description": "string",
        "location": "string",
        "modelCreatedAt": "string",
        "modelCreatorEmail": "string",
        "modelCreatorId": null,
        "modelCreatorName": "string",
        "modelName": "string"
      },
      "modelExecutionType": "dedicated",
      "modelId": "string",
      "modelKind": {
        "isAnomalyDetectionModel": true,
        "isCombinedModel": true,
        "isDecisionFlow": true,
        "isFeatureDiscovery": true,
        "isMultiseries": true,
        "isTimeSeries": true,
        "isUnsupervisedLearning": true
      },
      "name": "string",
      "permissions": [
        "string"
      ],
      "sourceMeta": {
        "decisionFlowId": "string",
        "decisionFlowVersionId": "string",
        "environmentUrl": "http://example.com",
        "fips_140_2Enabled": true,
        "projectCreatedAt": "string",
        "projectCreatorEmail": "string",
        "projectCreatorId": null,
        "projectCreatorName": "string",
        "projectId": "string",
        "projectName": "string",
        "scoringCode": {
          "dataRobotPredictionVersion": "string",
          "location": "local_leaderboard"
        },
        "useCaseDetails": {
          "createdAt": "string",
          "creatorEmail": "string",
          "creatorId": "string",
          "creatorName": "string",
          "id": "string",
          "name": "string"
        }
      },
      "target": {
        "classCount": 0,
        "classNames": [
          "string"
        ],
        "name": "string",
        "predictionProbabilitiesColumn": "string",
        "predictionThreshold": 1,
        "type": "Binary"
      },
      "timeseries": {
        "datetimeColumnFormat": "string",
        "datetimeColumnName": "string",
        "effectiveFeatureDerivationWindowEnd": 0,
        "effectiveFeatureDerivationWindowStart": 0,
        "featureDerivationWindowEnd": 0,
        "featureDerivationWindowStart": 0,
        "forecastDistanceColumnName": "string",
        "forecastDistances": [
          0
        ],
        "forecastDistancesTimeUnit": "MICROSECOND",
        "forecastPointColumnName": "string",
        "isCrossSeries": true,
        "isNewSeriesSupport": true,
        "isTraditionalTimeSeries": true,
        "seriesColumnName": "string"
      },
      "updatedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "userProvidedId": "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 [ModelPackageRetrieveResponse] true list of formatted model packages
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.

ModelPackageModelDescription

{
  "buildEnvironmentType": "DataRobot",
  "description": "string",
  "location": "string",
  "modelCreatedAt": "string",
  "modelCreatorEmail": "string",
  "modelCreatorId": null,
  "modelCreatorName": "string",
  "modelName": "string"
}

Properties

Name Type Required Restrictions Description
buildEnvironmentType string true build environment type of the model
description string¦null true a description of the model
location string¦null true location of the model
modelCreatedAt string¦null false time when the model was created
modelCreatorEmail string¦null false email of the user who created the model
modelCreatorId string¦null false ID of the creator of the model
modelCreatorName string¦null false name of the user who created the model
modelName string false model name

Enumerated Values

Property Value
buildEnvironmentType [DataRobot, Python, R, Java, Other]

ModelPackageModelKind

{
  "isAnomalyDetectionModel": true,
  "isCombinedModel": true,
  "isDecisionFlow": true,
  "isFeatureDiscovery": true,
  "isMultiseries": true,
  "isTimeSeries": true,
  "isUnsupervisedLearning": true
}

Properties

Name Type Required Restrictions Description
isAnomalyDetectionModel boolean true true if this is an anomaly detection model
isCombinedModel boolean true true if model is a combined model
isDecisionFlow boolean true true if this is a decision flow
isFeatureDiscovery boolean true true if this model uses the Feature Discovery feature
isMultiseries boolean true true if model is multiseries
isTimeSeries boolean true true if model is time series
isUnsupervisedLearning boolean true true if model used unsupervised learning

ModelPackageRetrieveResponse

{
  "activeDeploymentCount": 0,
  "buildStatus": "inProgress",
  "capabilities": {
    "supportsAutomaticActuals": true,
    "supportsChallengerModels": true,
    "supportsFeatureDriftTracking": true,
    "supportsHumilityRecommendedRules": true,
    "supportsHumilityRules": true,
    "supportsHumilityRulesDefaultCalculations": true,
    "supportsPredictionWarning": true,
    "supportsRetraining": true,
    "supportsScoringCodeDownload": true,
    "supportsSecondaryDatasets": true,
    "supportsSegmentedAnalysisDriftAndAccuracy": true,
    "supportsShapBasedPredictionExplanations": true,
    "supportsTargetDriftTracking": true
  },
  "datasets": {
    "baselineSegmentedBy": [
      "string"
    ],
    "datasetName": "string",
    "holdoutDataCatalogId": "string",
    "holdoutDataCatalogVersionId": "string",
    "holdoutDatasetName": "string",
    "targetHistogramBaseline": "predictions",
    "trainingDataCatalogId": "string",
    "trainingDataCatalogVersionId": "string",
    "trainingDataSize": 0
  },
  "id": "string",
  "importMeta": {
    "containsFearPipeline": true,
    "containsFeaturelists": true,
    "containsLeaderboardMeta": true,
    "containsProjectMeta": true,
    "creatorFullName": "string",
    "creatorId": "string",
    "creatorUsername": "string",
    "dateCreated": "string",
    "originalFileName": "string"
  },
  "isArchived": true,
  "isDeprecated": true,
  "mlpkgFileContents": {
    "allTimeSeriesPredictionIntervals": true
  },
  "modelDescription": {
    "buildEnvironmentType": "DataRobot",
    "description": "string",
    "location": "string",
    "modelCreatedAt": "string",
    "modelCreatorEmail": "string",
    "modelCreatorId": null,
    "modelCreatorName": "string",
    "modelName": "string"
  },
  "modelExecutionType": "dedicated",
  "modelId": "string",
  "modelKind": {
    "isAnomalyDetectionModel": true,
    "isCombinedModel": true,
    "isDecisionFlow": true,
    "isFeatureDiscovery": true,
    "isMultiseries": true,
    "isTimeSeries": true,
    "isUnsupervisedLearning": true
  },
  "name": "string",
  "permissions": [
    "string"
  ],
  "sourceMeta": {
    "decisionFlowId": "string",
    "decisionFlowVersionId": "string",
    "environmentUrl": "http://example.com",
    "fips_140_2Enabled": true,
    "projectCreatedAt": "string",
    "projectCreatorEmail": "string",
    "projectCreatorId": null,
    "projectCreatorName": "string",
    "projectId": "string",
    "projectName": "string",
    "scoringCode": {
      "dataRobotPredictionVersion": "string",
      "location": "local_leaderboard"
    },
    "useCaseDetails": {
      "createdAt": "string",
      "creatorEmail": "string",
      "creatorId": "string",
      "creatorName": "string",
      "id": "string",
      "name": "string"
    }
  },
  "target": {
    "classCount": 0,
    "classNames": [
      "string"
    ],
    "name": "string",
    "predictionProbabilitiesColumn": "string",
    "predictionThreshold": 1,
    "type": "Binary"
  },
  "timeseries": {
    "datetimeColumnFormat": "string",
    "datetimeColumnName": "string",
    "effectiveFeatureDerivationWindowEnd": 0,
    "effectiveFeatureDerivationWindowStart": 0,
    "featureDerivationWindowEnd": 0,
    "featureDerivationWindowStart": 0,
    "forecastDistanceColumnName": "string",
    "forecastDistances": [
      0
    ],
    "forecastDistancesTimeUnit": "MICROSECOND",
    "forecastPointColumnName": "string",
    "isCrossSeries": true,
    "isNewSeriesSupport": true,
    "isTraditionalTimeSeries": true,
    "seriesColumnName": "string"
  },
  "updatedBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "userProvidedId": "string"
}

Properties

Name Type Required Restrictions Description
activeDeploymentCount integer true Number of deployments currently using this model package
buildStatus string¦null false Model package build status
capabilities ModelPackageCapabilities true Capabilities of the current model package.
datasets ModelPackageDatasets true dataset information for the model package
id string true ID of the Model package
importMeta ModelPackageImportMeta true Information from when this Model Package was first saved
isArchived boolean true Whether the model package is permanently archived (cannot be used in deployment or replacement)
isDeprecated boolean true Whether the model package is deprecated. eg. python2 models are deprecated.
mlpkgFileContents MlpkgFileContents false Information about the content of .mlpkg artifact
modelDescription ModelPackageModelDescription true model description information for the model package
modelExecutionType string true Type of model package. dedicated (native DataRobot models) and custom_inference_model (user added inference models) both execute on DataRobot prediction servers, external do not
modelId string true ID of the model
modelKind ModelPackageModelKind true Model attribute information
name string true Model package name
permissions [string] true List of action permissions the user making the request has on the model package
sourceMeta ModelPackageSourceMeta true Meta information from where this model was generated
target ModelPackageTarget true target information for the model package
timeseries ModelPackageTimeseries true time series information for the model package
updatedBy UserMetadata true Information on the user who last modified the registered model
userProvidedId string false A user-provided unique ID associated with the given custom inference model.

Enumerated Values

Property Value
buildStatus [inProgress, complete, failed]
modelExecutionType [dedicated, custom_inference_model, external]

ModelPackageScoringCodeMeta

{
  "dataRobotPredictionVersion": "string",
  "location": "local_leaderboard"
}

Properties

Name Type Required Restrictions Description
dataRobotPredictionVersion string¦null true DataRobot prediction API version for the scoring code
location string¦null true Location of the scoring code

Enumerated Values

Property Value
location [local_leaderboard, mlpkg]

ModelPackageSourceMeta

{
  "decisionFlowId": "string",
  "decisionFlowVersionId": "string",
  "environmentUrl": "http://example.com",
  "fips_140_2Enabled": true,
  "projectCreatedAt": "string",
  "projectCreatorEmail": "string",
  "projectCreatorId": null,
  "projectCreatorName": "string",
  "projectId": "string",
  "projectName": "string",
  "scoringCode": {
    "dataRobotPredictionVersion": "string",
    "location": "local_leaderboard"
  },
  "useCaseDetails": {
    "createdAt": "string",
    "creatorEmail": "string",
    "creatorId": "string",
    "creatorName": "string",
    "id": "string",
    "name": "string"
  }
}

Properties

Name Type Required Restrictions Description
decisionFlowId string¦null true The ID of the flow associated with this model package
decisionFlowVersionId string¦null true The version ID of the flow associated with this model package
environmentUrl string(uri)¦null true If available, URL of the source model
fips_140_2Enabled boolean false true if the model was built with FIPS-140-2
projectCreatedAt string¦null false If available, time when the project was created
projectCreatorEmail string¦null false If available, email of the user who created the project
projectCreatorId string¦null false If available, ID of the creator of the project
projectCreatorName string¦null false If available, name of the user who created the project
projectId string¦null true If available, the project id used for this model
projectName string¦null true If available, the project name for this model
scoringCode ModelPackageScoringCodeMeta true If available, information about the model's scoring code
useCaseDetails UseCaseDetails false Details of the use-case associated to this registered model version

ModelPackageTarget

{
  "classCount": 0,
  "classNames": [
    "string"
  ],
  "name": "string",
  "predictionProbabilitiesColumn": "string",
  "predictionThreshold": 1,
  "type": "Binary"
}

Properties

Name Type Required Restrictions Description
classCount integer¦null true minimum: 0
Number of classes for classification models.
classNames [string]¦null true maxItems: 100
Class names for prediction results. When target type is Binary, two class names are returned. The first element is the minority (positive) class and the second element is the majority (negative) class. Limited to 100 returned for Multiclass.
name string true name of the target column
predictionProbabilitiesColumn string¦null true Field or column name containing prediction probabilities
predictionThreshold number¦null true maximum: 1
minimum: 0
Prediction threshold used for binary classification models
type string true Target type of the model.

Enumerated Values

Property Value
type [Binary, Regression, Multiclass, Multilabel, TextGeneration]

ModelPackageTimeseries

{
  "datetimeColumnFormat": "string",
  "datetimeColumnName": "string",
  "effectiveFeatureDerivationWindowEnd": 0,
  "effectiveFeatureDerivationWindowStart": 0,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "forecastDistanceColumnName": "string",
  "forecastDistances": [
    0
  ],
  "forecastDistancesTimeUnit": "MICROSECOND",
  "forecastPointColumnName": "string",
  "isCrossSeries": true,
  "isNewSeriesSupport": true,
  "isTraditionalTimeSeries": true,
  "seriesColumnName": "string"
}

Properties

Name Type Required Restrictions Description
datetimeColumnFormat string¦null true Date format for forecast date and forecast point column
datetimeColumnName string¦null true Name of the forecast date column
effectiveFeatureDerivationWindowEnd integer¦null true maximum: 0
Same concept as featureDerivationWindowEnd which is chosen by the user and based on the initial sampled data from the eda sample. When the dataset goes through aim, the pipeline reads the full dataset and figures out the "real" FDW (i.e., the effective FDW). For most models, eFDW is approximately the same as the FDW.
effectiveFeatureDerivationWindowStart integer¦null true maximum: 0
Same concept as featureDerivationWindowStart which is chosen by the user and based on the initial sampled data from the eda sample. When the dataset goes through aim, the pipeline reads the full dataset and figures out the "real" FDW (i.e., the effective FDW). For most models, eFDW is approximately the same as the FDW.
featureDerivationWindowEnd integer¦null true maximum: 0
Negative number or zero defining how many time units of the forecast distances time unit into the past relative to the forecast point the feature derivation window should end.
featureDerivationWindowStart integer¦null true maximum: 0
Negative number or zero defining how many time units of the forecast distances time unit into the past relative to the forecast point the feature derivation window should begin.
forecastDistanceColumnName string¦null true Name of the forecast distance column
forecastDistances [integer]¦null true List of integer forecast distances
forecastDistancesTimeUnit string¦null true The time unit of forecast distances
forecastPointColumnName string¦null true Name of the forecast point column
isCrossSeries boolean¦null true true if the model is cross-series.
isNewSeriesSupport boolean¦null true true if the model is optimized to support new series.
isTraditionalTimeSeries boolean¦null true true if the model is traditional time series.
seriesColumnName string¦null true Name of the series column in case of multi-series date

Enumerated Values

Property Value
forecastDistancesTimeUnit [MICROSECOND, MILLISECOND, SECOND, MINUTE, HOUR, DAY, WEEK, MONTH, QUARTER, YEAR]

ModelParametersRetrieveResponse

{
  "derivedFeatures": [
    {
      "coefficient": 0,
      "derivedFeature": "string",
      "originalFeature": "string",
      "stageCoefficients": [
        {
          "coefficient": 0,
          "stage": "string"
        }
      ],
      "transformations": [
        {
          "name": "string",
          "value": "string"
        }
      ],
      "type": "string"
    }
  ],
  "parameters": [
    {
      "name": "string",
      "value": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
derivedFeatures [DerivedFeatures] true An array of preprocessing information about derived features used in the model.
parameters [Parameters] true An array of parameters that are related to the whole model.

ModelRetrainResponse

{
  "message": "string"
}

Properties

Name Type Required Restrictions Description
message string true 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 was created.

ModelUpdate

{
  "isStarred": true,
  "predictionThreshold": 1
}

Properties

Name Type Required Restrictions Description
isStarred boolean false Mark model either as starred or unstarred.
predictionThreshold number false maximum: 1
minimum: 0
Threshold used for binary classification in predictions. Default value is 0.5.

ModelingJobListResponse

{
  "data": [
    {
      "blueprintId": "string",
      "featurelistId": "string",
      "id": "string",
      "isBlocked": true,
      "isTrainedOnGpu": true,
      "modelCategory": "model",
      "modelId": "string",
      "modelType": "string",
      "processes": [
        "string"
      ],
      "projectId": "string",
      "samplePct": 0,
      "status": "queue"
    }
  ]
}

Properties

Name Type Required Restrictions Description
data [ModelJobResponse] true List of modeling jobs.

NumIterationsTrainedData

{
  "numIterations": 0,
  "stage": "string"
}

Properties

Name Type Required Restrictions Description
numIterations integer true minimum: 0
The number of iterations run in this stage of modeling.
stage string¦null true Modeling stage or None if it is a single-stage model

NumIterationsTrainedResponse

{
  "data": [
    {
      "numIterations": 0,
      "stage": "string"
    }
  ],
  "modelId": "string",
  "projectId": "string"
}

Properties

Name Type Required Restrictions Description
data [NumIterationsTrainedData] true Number of estimators or iterations for a single model stage
modelId string true The model ID
projectId string true The project ID

OneMessageInfo

{
  "additionalInfo": [
    "string"
  ],
  "messageLevel": "CRITICAL",
  "messageText": "string"
}

Properties

Name Type Required Restrictions Description
additionalInfo [string] false maxItems: 50
Zero or more text strings for secondary display after user clicks for more information.
messageLevel string true Message severity level.
messageText string true maxLength: 500
minLength: 1
minLength: 1
Text for primary display in UI.

Enumerated Values

Property Value
messageLevel [CRITICAL, INFORMATIONAL, NO_ISSUES, WARNING]

Parameters

{
  "name": "string",
  "value": "string"
}

Properties

Name Type Required Restrictions Description
name string true The name of the parameter identifying what it means for the model, e.g. "Intercept".
value string true The value of the parameter.

ParetoFrontResponse

{
  "errorMetric": "string",
  "hyperparameters": {
    "buildingBlocks": {},
    "errorMetric": "string",
    "maxGenerations": 32,
    "numThreads": 0,
    "priorSolutions": [
      "string"
    ],
    "randomSeed": 0,
    "splitMode": "custom",
    "syncMigrations": true,
    "targetExpressionFormat": "None",
    "targetExpressionString": "string",
    "timeoutSec": 0,
    "trainingFraction": 1,
    "trainingSplitExpr": "string",
    "validationFraction": 1,
    "validationSplitExpr": "string",
    "weightExpr": "string"
  },
  "projectId": "string",
  "solutions": [
    {
      "bestModel": true,
      "complexity": 0,
      "error": 0,
      "eureqaSolutionId": "string",
      "expression": "string",
      "expressionAnnotated": "string"
    }
  ],
  "targetType": "Regression"
}

Properties

Name Type Required Restrictions Description
errorMetric string true The Eureqa error metric identifier used to compute error metrics for this search. Note that Eureqa error metrics do not correspond 1:1 with DataRobot error metrics - the available metrics are not the same, and even equivalent metrics may be computed slightly differently.
hyperparameters HyperparametersResponse¦null true The hyperparameters used by this run of the Eureqa blueprint.
projectId string true The project ID of the Eureqa model.
solutions [SolutionResponse] true The Eureqa model solutions.
targetType string true The type of the target variable.

Enumerated Values

Property Value
targetType [Regression, Binary]

PerFeatureMissingReport

{
  "feature": "string",
  "missingCount": 0,
  "missingPercentage": 1,
  "tasks": {
    "property1": {
      "descriptions": [
        "string"
      ],
      "name": "string"
    },
    "property2": {
      "descriptions": [
        "string"
      ],
      "name": "string"
    }
  },
  "type": "string"
}

Properties

Name Type Required Restrictions Description
feature string true The name of the feature
missingCount integer true The number of missing values in the training data
missingPercentage number true maximum: 1
minimum: 0
The percentage of missing values in the training data
tasks object true Information on individual tasks of the model which were used to process the feature. The names of properties will be task ids (which correspond to the ids used in the blueprint chart endpoints like GET /api/v2/projects/{projectId}/blueprints/{blueprintId}/blueprintChart/) The corresponding value for each task will be of the form task described.
» additionalProperties PerFeatureTaskMissingReport false none
type string true The type of the feature, e.g. Categorical or Numeric

PerFeatureTaskMissingReport

{
  "descriptions": [
    "string"
  ],
  "name": "string"
}

Properties

Name Type Required Restrictions Description
descriptions [string] true Human readable aggregated information about how the task handles missing values. The following descriptions may be present: what value is imputed for missing values, whether the feature being missing is treated as a feature by the task, whether missing values are treated as infrequent values, whether infrequent values are treated as missing values, and whether missing values are ignored.
name string true Task name, e.g. 'Ordinal encoding of categorical variables'

PlotDataResponse

{
  "actual": 0,
  "predicted": 0,
  "row": 0
}

Properties

Name Type Required Restrictions Description
actual number true The actual value of the target variable for the specified row.
predicted number true The predicted value of the target by the solution for the specified row.
row integer true The row number from the raw source data. Used as the X axis for the plot when rendered in the web application.

PredictionIntervalsCreate

{
  "percentiles": [
    0
  ]
}

Properties

Name Type Required Restrictions Description
percentiles [integer] true maxItems: 1
minItems: 1
The list of prediction intervals percentiles to calculate. Currently we only allow requesting one interval at a time.

PredictionIntervalsCreateResponse

{
  "message": "string"
}

Properties

Name Type Required Restrictions Description
message string true 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 was created.

PredictionIntervalsListResponse

{
  "count": 0,
  "data": [
    0
  ],
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalCount": 0
}

Properties

Name Type Required Restrictions Description
count integer false Number of items returned on this page.
data [integer] true A descending-ordered array of already-calculated prediction intervals percentiles.
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.

PrepareForDeployment

{
  "modelId": "string"
}

Properties

Name Type Required Restrictions Description
modelId string true The model to prepare for deployment.

PrimeFileCreate

{
  "language": "Python",
  "modelId": "string"
}

Properties

Name Type Required Restrictions Description
language string true The desired language of the generated code
modelId string true the Prime model to generate code for

Enumerated Values

Property Value
language [Python, Java]

PrimeFileListResponse

{
  "count": 0,
  "data": [
    {
      "id": "string",
      "isValid": true,
      "language": "Python",
      "modelId": "string",
      "parentModelId": "string",
      "projectId": "string",
      "rulesetId": 0
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties

Name Type Required Restrictions Description
count integer true number of items returned on this page
data [PrimeFileResponse] true each has the same schema as if retrieving the file individually from GET /api/v2/projects/(projectId)/primeFiles/(primeFileId)/.
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)

PrimeFileResponse

{
  "id": "string",
  "isValid": true,
  "language": "Python",
  "modelId": "string",
  "parentModelId": "string",
  "projectId": "string",
  "rulesetId": 0
}

Properties

Name Type Required Restrictions Description
id string true the ID of the file
isValid boolean true whether the code passed basic validation checks
language string true the language the code is written in (e.g. Python
modelId string true the Id of the Prime model
parentModelId string true the ID of the model this code approximates
projectId string true the ID of the project the file belongs to
rulesetId integer true the ID of the ruleset this code uses to approximate the parent model

Enumerated Values

Property Value
language [Python, Java]

PrimeInfoRetrieveResponse

{
  "canMakePrime": true,
  "message": "string",
  "messageId": 0
}

Properties

Name Type Required Restrictions Description
canMakePrime boolean true Indicating whether the requested model is a valid input for creating a Prime mode
message string true May contain details about why a model is not eligible for DataRobotPrime
messageId integer true An error code representing the reason the model cannot be approximated with DataRobot Prime; 0 for eligible models

PrimeModelCreatePayload

{
  "parentModelId": "string",
  "rulesetId": 0
}

Properties

Name Type Required Restrictions Description
parentModelId string true the model being approximated
rulesetId integer true the ID of the ruleset to use

PrimeModelDetailsRetrieveResponse

{
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "ruleCount": 0,
  "rulesetId": 0,
  "samplePct": 0,
  "samplingMethod": "random",
  "score": 0,
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Properties

Name Type Required Restrictions Description
blueprintId string true The blueprint used to construct the model.
dataSelectionMethod string false Identifies which setting defines the training size of the model when making predictions and scoring. Only used by datetime models.
featurelistId string¦null true the ID of the featurelist used by the model
featurelistName string¦null true the name of the featurelist used by the model.If null, the model was trained on multiple feature lists.
hasFinetuners boolean false Whether a model has fine tuners.
id string true the ID of the model
isAugmented boolean false Whether a model was trained using augmentation.
isFrozen boolean true Indicates whether the model is frozen, i.e., uses tuning parameters from a parent model.
isNClustersDynamicallyDetermined boolean false Whether number of clusters is dynamically determined. Only valid in unsupervised clustering projects.
isStarred boolean true whether the model has been starred
isTrainedIntoHoldout boolean true Indicates if model used holdout data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or whenthe model's training row count was greater than the max allowed validation size.
isTrainedIntoValidation boolean true Indicates if model used validation data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or when the model's training row count was greater than the max allowed training size.
lifecycle ModelLifecycle true Object returning model lifecycle.
linkFunction string¦null true The link function the final modeler uses in the blueprint. If no link function exists, returns null.
metrics object true the performance of the model according to various metrics, where each metric has validation, crossValidation, holdout, and training scores reported, or null if they have not been computed.
modelCategory string true Indicates the kind of model. Returns prime for DataRobot Prime models, blend for blender models, combined for combined models, and model for all other models.
modelFamily string true the family model belongs to, e.g. SVM, GBM, etc.
modelFamilyFullName string true The full name of the family that the model belongs to. For e.g., Support Vector Machine, Gradient Boosting Machine, etc.
modelNumber integer¦null true minimum: 0 (exclusive)
The model number from the leaderboard.
modelType string true identifies the model, e.g. Nystroem Kernel SVM Regressor
monotonicDecreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
monotonicIncreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
nClusters integer¦null false The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
parentModelId string¦null true The ID of the parent model if the model is frozen or a result of incremental learning. Null otherwise.
predictionThreshold number true maximum: 1
minimum: 0
threshold used for binary classification in predictions.
predictionThresholdReadOnly boolean true indicates whether modification of a predictions threshold is forbidden. Since v2.22 threshold modification is allowed.
processes [string]¦null true list of processes used by the model
projectId string true the ID of the project to which the model belongs
ruleCount integer true the number of rules used to create this model
rulesetId integer true the ID of the ruleset this model uses
samplePct number¦null true minimum: 0 (exclusive)
the percentage of the dataset used in training the model
samplingMethod string false indicates sampling method used to select training data in datetime models. For row-based project this is the way how requested number of rows are selected.For other projects (duration-based, start/end, project settings) - how specified percent of rows (timeWindowSamplePct) is selected from specified time window.
score number true the validation score of the models ruleset
supportsComposableMl boolean true indicates whether this model is supported in Composable ML.
supportsMonotonicConstraints boolean true whether this model supports enforcing monotonic constraints
timeWindowSamplePct integer¦null false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99, indicating the percentage of sampling within the time window. The points kept are determined by samplingMethod option. Will be null if no sampling was specified. Only used by datetime models.
trainingDuration string¦null true the duration spanned by the dates in the partition column for the data used to train the model
trainingEndDate string(date-time)¦null true the end date of the dates in the partition column for the data used to train the model
trainingRowCount integer¦null true minimum: 0 (exclusive)
The number of rows used to train the model.
trainingStartDate string(date-time)¦null true the start date of the dates in the partition column for the data used to train the model

Enumerated Values

Property Value
dataSelectionMethod [duration, rowCount, selectedDateRange, useProjectSettings]
modelCategory [model, prime, blend, combined, incrementalLearning]
samplingMethod [random, latest]

PrimeModelListResponse

{
  "count": 0,
  "data": [
    {
      "blueprintId": "string",
      "dataSelectionMethod": "duration",
      "featurelistId": "string",
      "featurelistName": "string",
      "hasFinetuners": true,
      "id": "string",
      "isAugmented": true,
      "isFrozen": true,
      "isNClustersDynamicallyDetermined": true,
      "isStarred": true,
      "isTrainedIntoHoldout": true,
      "isTrainedIntoValidation": true,
      "lifecycle": {
        "reason": "string",
        "stage": "active"
      },
      "linkFunction": "string",
      "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
      "modelCategory": "model",
      "modelFamily": "string",
      "modelFamilyFullName": "string",
      "modelNumber": 0,
      "modelType": "string",
      "monotonicDecreasingFeaturelistId": "string",
      "monotonicIncreasingFeaturelistId": "string",
      "nClusters": 0,
      "parentModelId": "string",
      "predictionThreshold": 1,
      "predictionThresholdReadOnly": true,
      "processes": [
        "string"
      ],
      "projectId": "string",
      "ruleCount": 0,
      "rulesetId": 0,
      "samplePct": 0,
      "samplingMethod": "random",
      "score": 0,
      "supportsComposableMl": true,
      "supportsMonotonicConstraints": true,
      "timeWindowSamplePct": 0,
      "trainingDuration": "string",
      "trainingEndDate": "2019-08-24T14:15:22Z",
      "trainingRowCount": 0,
      "trainingStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties

Name Type Required Restrictions Description
count integer true number of items returned on this page
data [PrimeModelDetailsRetrieveResponse] true each has the same schema as if retrieving the file individually from GET /api/v2/projects/(projectId)/primeFiles/(primeFileId)/.
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)

PrimeRulesetsCreatePayload

{}

Properties

None

PrimeRulesetsListResponse

{
  "modelId": "string",
  "parentModelId": "string",
  "projectId": "string",
  "ruleCount": 0,
  "rulesetId": 0,
  "score": 0
}

Properties

Name Type Required Restrictions Description
modelId string true the ID of the Prime model using this ruleset (if it exists) or null
parentModelId string true ID of the model this ruleset approximates
projectId string true the project this ruleset belongs to
ruleCount integer true the number of rules used by this ruleset
rulesetId integer true the ID of the ruleset
score number true the validation score of the ruleset

RatingTableCreateResponse

{
  "ratingTableId": "string",
  "ratingTableName": "string"
}

Properties

Name Type Required Restrictions Description
ratingTableId string true the ID of the newly created rating table
ratingTableName string true The name that was used for the rating table. May differ from the ratingTableName in the request, as names are trimmed and a suffix added to ensure all rating tables derived from the same model have unique names

RatingTableListResponse

{
  "count": 0,
  "data": [
    {
      "created": 0,
      "id": "string",
      "modelId": "string",
      "modelJobId": 0,
      "originalFilename": "string",
      "parentModelId": "string",
      "projectId": "string",
      "ratingTableName": "string",
      "validationError": "string",
      "validationJobId": "string",
      "validationWarnings": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties

Name Type Required Restrictions Description
count integer true the number of RatingTable objects returned
data [RatingTableRetrieveResponse] true the actual records. Each element of the array has the same schema
as if retrieving the table individually from
GET /api/v2/projects/(projectId)/ratingTables/(ratingTableId)/
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)

RatingTableModelDetailsResponse

{
  "blueprintId": "string",
  "dataSelectionMethod": "duration",
  "featurelistId": "string",
  "featurelistName": "string",
  "hasFinetuners": true,
  "id": "string",
  "isAugmented": true,
  "isFrozen": true,
  "isNClustersDynamicallyDetermined": true,
  "isStarred": true,
  "isTrainedIntoHoldout": true,
  "isTrainedIntoValidation": true,
  "lifecycle": {
    "reason": "string",
    "stage": "active"
  },
  "linkFunction": "string",
  "metrics": "\n        {\n            \"metrics\": {\n                \"RMSE\": {\n                    \"holdout\": 5000,\n                    \"validation\": 5100,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"crossValidation\": 6000,\n                    \"training\": null\n                },\n                \"FVE Poisson\": {\n                    \"holdout\": null,\n                    \"validation\": 0.56269,\n                    \"crossValidation\": 0.50166,\n                    \"backtesting\": null,\n                    \"backtestingScores\": null,\n                    \"training\": null\n                },\n            }\n        }\n",
  "modelCategory": "model",
  "modelFamily": "string",
  "modelFamilyFullName": "string",
  "modelNumber": 0,
  "modelType": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 0,
  "parentModelId": "string",
  "predictionThreshold": 1,
  "predictionThresholdReadOnly": true,
  "processes": [
    "string"
  ],
  "projectId": "string",
  "ratingTableId": "string",
  "samplePct": 0,
  "samplingMethod": "random",
  "supportsComposableMl": true,
  "supportsMonotonicConstraints": true,
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z"
}

Properties

Name Type Required Restrictions Description
blueprintId string true The blueprint used to construct the model.
dataSelectionMethod string false Identifies which setting defines the training size of the model when making predictions and scoring. Only used by datetime models.
featurelistId string¦null true the ID of the featurelist used by the model
featurelistName string¦null true the name of the featurelist used by the model.If null, the model was trained on multiple feature lists.
hasFinetuners boolean false Whether a model has fine tuners.
id string true the ID of the model
isAugmented boolean false Whether a model was trained using augmentation.
isFrozen boolean true Indicates whether the model is frozen, i.e., uses tuning parameters from a parent model.
isNClustersDynamicallyDetermined boolean false Whether number of clusters is dynamically determined. Only valid in unsupervised clustering projects.
isStarred boolean true whether the model has been starred
isTrainedIntoHoldout boolean true Indicates if model used holdout data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or whenthe model's training row count was greater than the max allowed validation size.
isTrainedIntoValidation boolean true Indicates if model used validation data for training. This can happen for time-aware models using trainingStartDate/trainingEndDate parameters or when the model's training row count was greater than the max allowed training size.
lifecycle ModelLifecycle true Object returning model lifecycle.
linkFunction string¦null true The link function the final modeler uses in the blueprint. If no link function exists, returns null.
metrics object true the performance of the model according to various metrics, where each metric has validation, crossValidation, holdout, and training scores reported, or null if they have not been computed.
modelCategory string true Indicates the kind of model. Returns prime for DataRobot Prime models, blend for blender models, combined for combined models, and model for all other models.
modelFamily string true the family model belongs to, e.g. SVM, GBM, etc.
modelFamilyFullName string true The full name of the family that the model belongs to. For e.g., Support Vector Machine, Gradient Boosting Machine, etc.
modelNumber integer¦null true minimum: 0 (exclusive)
The model number from the leaderboard.
modelType string true identifies the model, e.g. Nystroem Kernel SVM Regressor
monotonicDecreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
monotonicIncreasingFeaturelistId string¦null true the ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
nClusters integer¦null false The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
parentModelId string¦null true The ID of the parent model if the model is frozen or a result of incremental learning. Null otherwise.
predictionThreshold number true maximum: 1
minimum: 0

threshold used for binary classification in predictions.
predictionThresholdReadOnly boolean true indicates whether modification of a predictions threshold is forbidden. Since v2.22 threshold modification is allowed.
processes [string]¦null true list of processes used by the model
projectId string true the ID of the project to which the model belongs
ratingTableId string true The rating table ID
samplePct number¦null true minimum: 0 (exclusive)
the percentage of the dataset used in training the model
samplingMethod string false indicates sampling method used to select training data in datetime models. For row-based project this is the way how requested number of rows are selected.For other projects (duration-based, start/end, project settings) - how specified percent of rows (timeWindowSamplePct) is selected from specified time window.
supportsComposableMl boolean true indicates whether this model is supported in Composable ML.
supportsMonotonicConstraints boolean true whether this model supports enforcing monotonic constraints
timeWindowSamplePct integer¦null false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99, indicating the percentage of sampling within the time window. The points kept are determined by samplingMethod option. Will be null if no sampling was specified. Only used by datetime models.
trainingDuration string¦null true the duration spanned by the dates in the partition column for the data used to train the model
trainingEndDate string(date-time)¦null true the end date of the dates in the partition column for the data used to train the model
trainingRowCount integer¦null true minimum: 0 (exclusive)
The number of rows used to train the model.
trainingStartDate string(date-time)¦null true the start date of the dates in the partition column for the data used to train the model

Enumerated Values

Property Value
dataSelectionMethod [duration, rowCount, selectedDateRange, useProjectSettings]
modelCategory [model, prime, blend, combined, incrementalLearning]
samplingMethod [random, latest]

RatingTableRetrieveResponse

{
  "created": 0,
  "id": "string",
  "modelId": "string",
  "modelJobId": 0,
  "originalFilename": "string",
  "parentModelId": "string",
  "projectId": "string",
  "ratingTableName": "string",
  "validationError": "string",
  "validationJobId": "string",
  "validationWarnings": "string"
}

Properties

Name Type Required Restrictions Description
created number true ISO-8601 timestamp of when the rating table record was created.
id string true the ID of the rating table record
modelId string true the model ID of a model that was created from the rating table.
May be null if a model has not been created from the rating table.
modelJobId integer true the qid of the job to create a model from this rating table.
Can be null if a model has not been created from the rating table.
originalFilename string true the filename of the uploaded rating table file
parentModelId string true the model ID of the model the rating table was modified from
projectId string true the project ID of the rating table record
ratingTableName string true the name of the rating table
validationError string true rating table validation error messages. If the rating table
was validated successfully, it will be an empty string.
validationJobId string true the qid of the created job to validate the rating table.
Can be null if the rating table has not been validated.
validationWarnings string true rating table validation warning messages.

RatingTableUpdate

{
  "ratingTableName": "string"
}

Properties

Name Type Required Restrictions Description
ratingTableName string true the name of the new model

Reasons

{
  "supportsDocumentTextExtractionSampleInsight": "string",
  "supportsImageActivationMaps": "string",
  "supportsImageEmbedding": "string",
  "supportsLiftChart": "string",
  "supportsResiduals": "string",
  "supportsRocCurve": "string"
}

Properties

Name Type Required Restrictions Description
supportsDocumentTextExtractionSampleInsight string false If present, the reason document text extraction sample insights are not supported for the model.
supportsImageActivationMaps string false If present, the reason image activation maps are not supported for the model.
supportsImageEmbedding string false If present, the reason image embeddings are not supported for the model.
supportsLiftChart string false If present, the reason why Lift Chart cannot be generated for the model. There are some cases where Lift Chart is available but it was calculated using stacked predictions or in-sample predictions.
supportsResiduals string false If present, the reason why residuals are not available for the model. There are some cases where Residuals are available but they were calculated using stacked predictions or in-sample predictions.
supportsRocCurve string false If present, the reason why ROC Curve cannot be generated for the model. There are some cases where ROC Curve is available but it was calculated using stacked predictions or in-sample predictions.

RecommendedModelResponse

{
  "modelId": "string",
  "recommendationType": "MOSTACCURATE"
}

Properties

Name Type Required Restrictions Description
modelId string true the ID of the recommended model
recommendationType string true the type of model recommendation

Enumerated Values

Property Value
recommendationType [MOSTACCURATE, LIMITEDACCURATE, FASTACCURATE, RECOMMENDEDFORDEPLOYMENT, PREPAREDFORDEPLOYMENT]

RegisteredModelCreatedBy

{
  "email": "string",
  "id": "string",
  "name": "string"
}

Properties

Name Type Required Restrictions Description
email string true Email of the user that created the registered model
id string true ID of user that created the registered model
name string¦null true Full name of the user that created the registered model

RegisteredModelDeploymentResponse

{
  "createdAt": "string",
  "createdBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "currentlyDeployed": true,
  "firstDeployedAt": "string",
  "firstDeployedBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "id": "string",
  "isChallenger": true,
  "label": "string",
  "predictionEnvironment": {
    "id": "string",
    "isManagedByManagementAgent": true,
    "name": "string",
    "platform": "aws",
    "plugin": "string",
    "supportedModelFormats": [
      "datarobot"
    ]
  },
  "registeredModelVersion": 0,
  "status": "string"
}

Properties

Name Type Required Restrictions Description
createdAt string true Deployment creation date
createdBy UserMetadata true Information on the creator of the deployment
currentlyDeployed boolean true Whether version of this registered model is currently deployed
firstDeployedAt string¦null true When version of this registered model was first deployed
firstDeployedBy UserMetadata true Information on the user who first deployed the version of this registered model
id string true ID of the deployment
isChallenger boolean true True if given version is a challenger in a given deployment
label string¦null true Label of the deployment
predictionEnvironment DeploymentPredictionEnvironmentResponse false Information related to the current PredictionEnvironment.
registeredModelVersion integer true Version of the registered model
status string true Status of the deployment

RegisteredModelDeploymentsListResponse

{
  "count": 0,
  "data": [
    {
      "createdAt": "string",
      "createdBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "currentlyDeployed": true,
      "firstDeployedAt": "string",
      "firstDeployedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "id": "string",
      "isChallenger": true,
      "label": "string",
      "predictionEnvironment": {
        "id": "string",
        "isManagedByManagementAgent": true,
        "name": "string",
        "platform": "aws",
        "plugin": "string",
        "supportedModelFormats": [
          "datarobot"
        ]
      },
      "registeredModelVersion": 0,
      "status": "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 [RegisteredModelDeploymentResponse] true List of formatted deployments
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.

RegisteredModelListResponse

{
  "count": 0,
  "data": [
    {
      "createdAt": "2019-08-24T14:15:22Z",
      "createdBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "description": "string",
      "id": "string",
      "isArchived": true,
      "isGlobal": true,
      "lastVersionNum": 0,
      "modifiedAt": "2019-08-24T14:15:22Z",
      "modifiedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "name": "string",
      "target": {
        "name": "string",
        "type": "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 [RegisteredModelResponse] true List of formatted registered models
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.

RegisteredModelResponse

{
  "createdAt": "2019-08-24T14:15:22Z",
  "createdBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "description": "string",
  "id": "string",
  "isArchived": true,
  "isGlobal": true,
  "lastVersionNum": 0,
  "modifiedAt": "2019-08-24T14:15:22Z",
  "modifiedBy": {
    "email": "string",
    "id": "string",
    "name": "string"
  },
  "name": "string",
  "target": {
    "name": "string",
    "type": "string"
  }
}

Properties

Name Type Required Restrictions Description
createdAt string(date-time) true Date when the registered model was created
createdBy RegisteredModelCreatedBy true Information on the creator of the registered model
description string¦null false Description of the registered model
id string true ID of the registered model
isArchived boolean true Whether the model is archived
isGlobal boolean false Whether the registered model is global (accessible to all users in the organization) or local(accessible only to the owner and the users with whom it has been explicitly shared)
lastVersionNum integer true Latest version associated to this registered model
modifiedAt string(date-time) true Date when the registered model was last modified
modifiedBy UserMetadata true Information on the user who last modified the registered model
name string true Name of the registered model
target RegisteredModelTarget true Information on the target variable

RegisteredModelTarget

{
  "name": "string",
  "type": "string"
}

Properties

Name Type Required Restrictions Description
name string true Name of the target variable
type string¦null true Type of the target variable

RegisteredModelUpdate

{
  "description": "string",
  "isGlobal": true,
  "name": "string"
}

Properties

Name Type Required Restrictions Description
description string false maxLength: 2048
Description of the registered model
isGlobal boolean false Make registered model global (accessible to all users in the organization) or local(accessible only to the owner and the users with whom it has been explicitly shared)
name string false maxLength: 1024
Name of the registered model

RegisteredModelVersionsListResponse

{
  "count": 0,
  "data": [
    {
      "activeDeploymentCount": 0,
      "buildStatus": "inProgress",
      "capabilities": {
        "supportsAutomaticActuals": true,
        "supportsChallengerModels": true,
        "supportsFeatureDriftTracking": true,
        "supportsHumilityRecommendedRules": true,
        "supportsHumilityRules": true,
        "supportsHumilityRulesDefaultCalculations": true,
        "supportsPredictionWarning": true,
        "supportsRetraining": true,
        "supportsScoringCodeDownload": true,
        "supportsSecondaryDatasets": true,
        "supportsSegmentedAnalysisDriftAndAccuracy": true,
        "supportsShapBasedPredictionExplanations": true,
        "supportsTargetDriftTracking": true
      },
      "datasets": {
        "baselineSegmentedBy": [
          "string"
        ],
        "datasetName": "string",
        "holdoutDataCatalogId": "string",
        "holdoutDataCatalogVersionId": "string",
        "holdoutDatasetName": "string",
        "targetHistogramBaseline": "predictions",
        "trainingDataCatalogId": "string",
        "trainingDataCatalogVersionId": "string",
        "trainingDataSize": 0
      },
      "id": "string",
      "importMeta": {
        "containsFearPipeline": true,
        "containsFeaturelists": true,
        "containsLeaderboardMeta": true,
        "containsProjectMeta": true,
        "creatorFullName": "string",
        "creatorId": "string",
        "creatorUsername": "string",
        "dateCreated": "string",
        "originalFileName": "string"
      },
      "isArchived": true,
      "isDeprecated": true,
      "mlpkgFileContents": {
        "allTimeSeriesPredictionIntervals": true
      },
      "modelDescription": {
        "buildEnvironmentType": "DataRobot",
        "description": "string",
        "location": "string",
        "modelCreatedAt": "string",
        "modelCreatorEmail": "string",
        "modelCreatorId": null,
        "modelCreatorName": "string",
        "modelName": "string"
      },
      "modelExecutionType": "dedicated",
      "modelId": "string",
      "modelKind": {
        "isAnomalyDetectionModel": true,
        "isCombinedModel": true,
        "isDecisionFlow": true,
        "isFeatureDiscovery": true,
        "isMultiseries": true,
        "isTimeSeries": true,
        "isUnsupervisedLearning": true
      },
      "name": "string",
      "permissions": [
        "string"
      ],
      "sourceMeta": {
        "decisionFlowId": "string",
        "decisionFlowVersionId": "string",
        "environmentUrl": "http://example.com",
        "fips_140_2Enabled": true,
        "projectCreatedAt": "string",
        "projectCreatorEmail": "string",
        "projectCreatorId": null,
        "projectCreatorName": "string",
        "projectId": "string",
        "projectName": "string",
        "scoringCode": {
          "dataRobotPredictionVersion": "string",
          "location": "local_leaderboard"
        },
        "useCaseDetails": {
          "createdAt": "string",
          "creatorEmail": "string",
          "creatorId": "string",
          "creatorName": "string",
          "id": "string",
          "name": "string"
        }
      },
      "target": {
        "classCount": 0,
        "classNames": [
          "string"
        ],
        "name": "string",
        "predictionProbabilitiesColumn": "string",
        "predictionThreshold": 1,
        "type": "Binary"
      },
      "timeseries": {
        "datetimeColumnFormat": "string",
        "datetimeColumnName": "string",
        "effectiveFeatureDerivationWindowEnd": 0,
        "effectiveFeatureDerivationWindowStart": 0,
        "featureDerivationWindowEnd": 0,
        "featureDerivationWindowStart": 0,
        "forecastDistanceColumnName": "string",
        "forecastDistances": [
          0
        ],
        "forecastDistancesTimeUnit": "MICROSECOND",
        "forecastPointColumnName": "string",
        "isCrossSeries": true,
        "isNewSeriesSupport": true,
        "isTraditionalTimeSeries": true,
        "seriesColumnName": "string"
      },
      "updatedBy": {
        "email": "string",
        "id": "string",
        "name": "string"
      },
      "userProvidedId": "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 [ModelPackageRetrieveResponse] true List of formatted registered model's versions
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.

RetrainDatetimeModel

{
  "featurelistId": "string",
  "modelId": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 2,
  "samplingMethod": "random",
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z",
  "useProjectSettings": true
}

Properties

Name Type Required Restrictions Description
featurelistId string false If specified, the new model will be trained using this featurelist. Otherwise, the model will be trained on the same feature list as the source model.
modelId string true The ID of an existing model to use as the source for the training parameters.
monotonicDecreasingFeaturelistId string¦null false The ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
monotonicIncreasingFeaturelistId string¦null false The ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
nClusters integer false maximum: 100
minimum: 2

The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
samplingMethod string false Defines how training data is selected if subsampling is used (e.g., if timeWindowSamplePct is specified). Can be either random or latest. If omitted, defaults to latest if trainingRowCount is used and random for other cases (e.g., if trainingDuration or useProjectSettings is specified). May only be specified for OTV projects.
timeWindowSamplePct integer false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99 indicating the percentage of sampling within the time window. The points kept are determined by the value provided for the samplingMethod option. If specified, trainingRowCount may not be specified, and the specified model must either be a duration or selectedDateRange model, or one of trainingDuration or trainingStartDate and trainingEndDate must be specified.
trainingDuration string(duration) false A duration string representing the training duration to use for training the new model. If specified, the model will be trained using the specified training duration. Otherwise, the original model's duration will be used. Only one of trainingRowCount, trainingDuration, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.
trainingEndDate string(date-time) false A datetime string representing the end date of the data to use for training this model. Note that only one of trainingDuration or trainingRowCount or trainingStartDate and trainingEndDate should be specified. If trainingStartDate and trainingEndDate are specified, the source model must be frozen.
trainingRowCount integer false minimum: 0 (exclusive)
The number of rows of data that should be used to train the model. If not specified, the original model's row count will be used. Only one of trainingRowCount, trainingDuration, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.
trainingStartDate string(date-time) false A datetime string representing the start date of the data to use for training this model. Note that only one of trainingDuration or trainingRowCount or trainingStartDate and trainingEndDate should be specified. If trainingStartDate and trainingEndDate are specified, the source model must be frozen.
useProjectSettings boolean false If True, the model will be trained using the previously-specified custom backtest training settings. Only one of trainingRowCount, trainingDuration, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.

Enumerated Values

Property Value
samplingMethod [random, latest]

RetrainModel

{
  "featurelistId": "string",
  "modelId": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 2,
  "samplePct": 0,
  "scoringType": "validation",
  "trainingRowCount": 0
}

Properties

Name Type Required Restrictions Description
featurelistId string false If specified, the model will be trained using that featurelist, otherwise the model will be trained on the same feature list as before.
modelId string true The model to be retrained
monotonicDecreasingFeaturelistId string¦null false The ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.
monotonicIncreasingFeaturelistId string¦null false The ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.
nClusters integer false maximum: 100
minimum: 2
The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
samplePct number false The percentage of the dataset to use to use to train the model. The specified percentage should be between 0 and 100. If not specified, original model sample percent will be used.
scoringType string false Validation is available for any partitioning. If the project uses cross validation, crossValidation may be used to indicate that all available training/validation combinations should be used.
trainingRowCount integer false The number of rows to use to train the model. If not specified, original model training row count will be used.

Enumerated Values

Property Value
scoringType [validation, crossValidation]

RuleFitCodeFileCreate

{
  "language": "Python",
  "modelId": "string"
}

Properties

Name Type Required Restrictions Description
language string true The desired language of the generated code
modelId string true the RuleFit model to generate code for

Enumerated Values

Property Value
language [Python, Java]

RuleFitCodeFileListResponse

{
  "count": 0,
  "data": [
    {
      "id": "string",
      "isValid": true,
      "language": "Python",
      "modelId": "string",
      "projectId": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties

Name Type Required Restrictions Description
count integer true number of items returned on this page
data [RuleFitCodeFileResponse] true each has the same schema as if retrieving the file individually from GET /api/v2/projects/(projectId)/ruleFitFiles/(ruleFitFileId)/.
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)

RuleFitCodeFileResponse

{
  "id": "string",
  "isValid": true,
  "language": "Python",
  "modelId": "string",
  "projectId": "string"
}

Properties

Name Type Required Restrictions Description
id string true the ID of the file
isValid boolean true whether the code passed basic validation checks
language string true the language the code is written in (e.g. Python
modelId string true the ID of the RuleFit model
projectId string true the ID of the project the file belongs to

Enumerated Values

Property Value
language [Python, Java]

SegmentChampionModelUpdate

{
  "clone": false,
  "modelId": "string"
}

Properties

Name Type Required Restrictions Description
clone boolean false Clone current combined model and assign champion to the new combined model.
modelId string true The ID of segment champion model.

SegmentChampionModelUpdateResponse

{
  "combinedModelId": "string"
}

Properties

Name Type Required Restrictions Description
combinedModelId string true The ID of the combined model that has been updated.

SegmentProjectModelResponse

{
  "modelId": "string",
  "projectId": "string",
  "segment": "string"
}

Properties

Name Type Required Restrictions Description
modelId string¦null true ID of segment champion model.
projectId string¦null true ID of the project used for this segment.
segment string true Segment name.

Select

{
  "supportsGridSearch": true,
  "values": [
    "string"
  ]
}

Properties

Name Type Required Restrictions Description
supportsGridSearch boolean true When True, Grid Search is supported for this parameter.
values [string] true List of valid values for this field.

SharedRolesUpdate

{
  "operation": "updateRoles",
  "roles": [
    {
      "role": "string",
      "shareRecipientType": "user",
      "username": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
operation string true Name of the action being taken. The only operation is 'updateRoles'.
roles [oneOf] true maxItems: 100
minItems: 1
Array of GrantAccessControl objects., up to maximum 100 objects.

oneOf

Name Type Required Restrictions Description
» anonymous GrantAccessControlWithUsername false none

xor

Name Type Required Restrictions Description
» anonymous GrantAccessControlWithId false none

Enumerated Values

Property Value
operation updateRoles

SharingListResponse

{
  "count": 0,
  "data": [
    {
      "canShare": true,
      "role": "string",
      "userId": "string",
      "username": "string"
    }
  ],
  "next": "string",
  "previous": "string"
}

Properties

Name Type Required Restrictions Description
count integer true The number of items returned.
data [AccessControl] true The access control list.
next string¦null true URL pointing to the next page.
previous string¦null true URL pointing to the previous page.

SharingListV2Response

{
  "count": 0,
  "data": [
    {
      "id": "string",
      "name": "string",
      "role": "ADMIN",
      "shareRecipientType": "user"
    }
  ],
  "next": "string",
  "previous": "string",
  "totalCount": 0
}

Properties

Name Type Required Restrictions Description
count integer true The number of items returned.
data [AccessControlV2] true The access control list.
next string¦null true URL pointing to the next page.
previous string¦null true URL pointing to the previous page.
totalCount integer true Total number of items matching the condition.

SharingUpdateOrRemoveWithGrant

{
  "data": [
    {
      "canShare": true,
      "role": "ADMIN",
      "username": "string"
    }
  ]
}

Properties

Name Type Required Restrictions Description
data [UserRoleWithGrant] true maxItems: 100
List of sharing roles to update.

SolutionResponse

{
  "bestModel": true,
  "complexity": 0,
  "error": 0,
  "eureqaSolutionId": "string",
  "expression": "string",
  "expressionAnnotated": "string"
}

Properties

Name Type Required Restrictions Description
bestModel boolean true True if this solution generates the best model.
complexity integer true The complexity score for this solution. Complexity score is a function of the mathematical operators used in the current solution. The complexity calculation can be tuned via model hyperparameters.
error number¦null true The error for the current solution, as computed by eureqa using the errorMetric error metric. None if Eureqa model refitted existing solutions.
eureqaSolutionId string true The ID of the solution.
expression string true The eureqa "solution string". This is a mathematical expression; human-readable but with strict syntax specifications defined by Eureqa.
expressionAnnotated string true The expression, rendered with additional tags to assist in automatic parsing.

StageCoefficients

{
  "coefficient": 0,
  "stage": "string"
}

Properties

Name Type Required Restrictions Description
coefficient number true The corresponding value of the coefficient for that stage.
stage string true The name of the stage.

TrainDatetimeFrozenModel

{
  "modelId": "string",
  "samplingMethod": "random",
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingEndDate": "2019-08-24T14:15:22Z",
  "trainingRowCount": 0,
  "trainingStartDate": "2019-08-24T14:15:22Z",
  "useProjectSettings": true
}

Properties

Name Type Required Restrictions Description
modelId string true The ID of an existing model to use as the source for the training parameters.
samplingMethod string false Defines how training data is selected if subsampling is used (e.g., if timeWindowSamplePct is specified). Can be either random or latest. If omitted, defaults to latest if trainingRowCount is used and random for other cases (e.g., if trainingDuration or useProjectSettings is specified). May only be specified for OTV projects.
timeWindowSamplePct integer false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99 indicating the percentage of sampling within the time window. The points kept are determined by the value provided for the samplingMethod option. If specified, trainingRowCount may not be specified, and the specified model must either be a duration or selectedDateRange model, or one of trainingDuration or trainingStartDate and trainingEndDate must be specified.
trainingDuration string(duration) false A duration string representing the training duration for the submitted model. Only one of trainingDuration, trainingRowCount, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.
trainingEndDate string(date-time) false A datetime string representing the end date of the data to use for training this model. If specified, trainingStartDate must also be specified. Only one of trainingDuration, trainingRowCount, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.
trainingRowCount integer false minimum: 0 (exclusive)
The number of rows of data that should be used when training this model. Only one of trainingDuration, trainingRowCount, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.
trainingStartDate string(date-time) false A datetime string representing the start date of the data to use for training this model. If specified, trainingEndDate must also be specified. Only one of trainingDuration, trainingRowCount, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.
useProjectSettings boolean false If True, the model will be trained using the previously-specified custom backtest training settings. Only one of trainingDuration, trainingRowCount, trainingStartDate and trainingEndDate, or useProjectSettings may be specified.

Enumerated Values

Property Value
samplingMethod [random, latest]

TrainDatetimeModel

{
  "blueprintId": "string",
  "featurelistId": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 2,
  "samplingMethod": "random",
  "sourceProjectId": "string",
  "timeWindowSamplePct": 0,
  "trainingDuration": "string",
  "trainingRowCount": 0,
  "useProjectSettings": true
}

Properties

Name Type Required Restrictions Description
blueprintId string true The ID of a blueprint to use to generate the model. Allowed blueprints can be retrieved using GET /api/v2/projects/{projectId}/blueprints/ or taken from existing models.
featurelistId string false If specified, the model will be trained using this featurelist. If not specified, the recommended featurelist for the specified blueprint will be used. If there is no recommended featurelist, the project's default will be used.
monotonicDecreasingFeaturelistId string¦null false The ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no constraints will be enforced. If omitted, the project default is used. May only be specified for OTV projects.
monotonicIncreasingFeaturelistId string¦null false The ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no constraints will be enforced. If omitted, the project default is used. May only be specified for OTV projects.
nClusters integer false maximum: 100
minimum: 2
The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
samplingMethod string false Defines how training data is selected if subsampling is used (e.g., if timeWindowSamplePct is specified). Can be either random or latest. If omitted, defaults to latest if trainingRowCount is used and random for other cases (e.g., if trainingDuration or useProjectSettings is specified). May only be specified for OTV projects.
sourceProjectId string false The project the blueprint comes from. Required only if the blueprintId comes from a different project.
timeWindowSamplePct integer false maximum: 100 (exclusive)
minimum: 0 (exclusive)
An integer between 1 and 99 indicating the percentage of sampling within the time window. The points kept are determined by the value provided for the samplingMethod option. If specified, trainingRowCount may not be specified, and the specified model must either be a duration or selectedDateRange model, or one of trainingDuration or trainingStartDate and trainingEndDate must be specified.
trainingDuration string(duration) false A duration string representing the training duration for the submitted model.
trainingRowCount integer false minimum: 0 (exclusive)
The number of rows of data that should be used when training this model.
useProjectSettings boolean false If True, the model will be trained using the previously-specified custom backtest training settings.

Enumerated Values

Property Value
samplingMethod [random, latest]

TrainModel

{
  "blueprintId": "string",
  "featurelistId": "string",
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "nClusters": 2,
  "samplePct": 0,
  "scoringType": "validation",
  "sourceProjectId": "string",
  "trainingRowCount": 0
}

Properties

Name Type Required Restrictions Description
blueprintId string true The ID of a blueprint to use to generate the model. Allowed blueprints can be retrieved using GET /api/v2/projects/{projectId}/blueprints/ or taken from existing models.
featurelistId string false If specified, the model will be trained using this featurelist. If not specified, the recommended featurelist for the specified blueprint will be used. If there is no recommended featurelist, the project's default will be used.
monotonicDecreasingFeaturelistId string¦null false The ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no constraints will be enforced. If omitted, the project default is used.
monotonicIncreasingFeaturelistId string¦null false The ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no constraints will be enforced. If omitted, the project default is used.
nClusters integer false maximum: 100
minimum: 2
The number of clusters to use in the specified unsupervised clustering model. Only valid in unsupervised clustering projects.
samplePct number false maximum: 100
minimum: 0 (exclusive)
The percentage of the dataset to use with the model. Only one of samplePct and trainingRowCount should be specified. The specified percentage should be between 0 and 100.
scoringType string false Validation is available for any partitioning. If the project uses cross validation, crossValidation may be used to indicate that all available training/validation combinations should be used.
sourceProjectId string false The project the blueprint comes from. Required only if the blueprintId comes from a different project.
trainingRowCount integer false An integer representing the number of rows of the dataset to use with the model. Only one of samplePct and trainingRowCount should be specified.

Enumerated Values

Property Value
scoringType [validation, crossValidation]

TrainingHistoryEntry

{
  "creationDate": "string",
  "lid": "string",
  "pid": "string",
  "projectModelsCount": 0,
  "projectName": "string",
  "targetName": "string"
}

Properties

Name Type Required Restrictions Description
creationDate string true ISO-8601 timestamp of when the project the blueprint was trained on was created.
lid string true The leaderboard ID the blueprint was trained on.
pid string true The project ID the blueprint was trained on.
projectModelsCount integer true Number of models in the project the blueprint was trained on.
projectName string true The project name the blueprint was trained on.
targetName string true The target name of the project the blueprint was trained on.

TrainingInfoResponse

{
  "holdoutTrainingDuration": "string",
  "holdoutTrainingEndDate": "2019-08-24T14:15:22Z",
  "holdoutTrainingRowCount": 0,
  "holdoutTrainingStartDate": "2019-08-24T14:15:22Z",
  "predictionTrainingDuration": "string",
  "predictionTrainingEndDate": "2019-08-24T14:15:22Z",
  "predictionTrainingRowCount": 0,
  "predictionTrainingStartDate": "2019-08-24T14:15:22Z"
}

Properties

Name Type Required Restrictions Description
holdoutTrainingDuration string(duration) true the duration of the data used to train a model to score the holdout
holdoutTrainingEndDate string(date-time) true the end date of the data used to train a model to score the holdout
holdoutTrainingRowCount integer true the number of rows used to train a model to score the holdout
holdoutTrainingStartDate string(date-time) true the start date of data used to train a model to score the holdout
predictionTrainingDuration string(duration) true the duration of the data used to train a model to make predictions
predictionTrainingEndDate string(date-time) true the end date of the data used to train a model to make predictions
predictionTrainingRowCount integer true the number of rows used to train a model to make predictions
predictionTrainingStartDate string(date-time) true the start date of data used to train a model to make predictions

Transformations

{
  "name": "string",
  "value": "string"
}

Properties

Name Type Required Restrictions Description
name string true The name of the transformation.
value string true The value used in carrying it out.

TuningParameter

{
  "parameterId": "string",
  "value": "string"
}

Properties

Name Type Required Restrictions Description
parameterId string true ID of the parameter whose value to set.
value any true Value for the specified parameter.

oneOf

Name Type Required Restrictions Description
» anonymous any false none

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 boolean false none

or

Name Type Required Restrictions Description
»» anonymous number false none

xor

Name Type Required Restrictions Description
» anonymous [anyOf] false none

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 boolean false none

or

Name Type Required Restrictions Description
»» anonymous number false none

TuningParameters

{
  "constraints": {
    "ascii": {
      "supportsGridSearch": true
    },
    "float": {
      "max": 0,
      "min": 0,
      "supportsGridSearch": true
    },
    "floatList": {
      "maxLength": 0,
      "maxVal": 0,
      "minLength": 0,
      "minVal": 0,
      "supportsGridSearch": true
    },
    "int": {
      "max": 0,
      "min": 0,
      "supportsGridSearch": true
    },
    "intList": {
      "maxLength": 0,
      "maxVal": 0,
      "minLength": 0,
      "minVal": 0,
      "supportsGridSearch": true
    },
    "select": {
      "supportsGridSearch": true,
      "values": [
        "string"
      ]
    },
    "selectgrid": {
      "supportsGridSearch": true,
      "values": [
        "string"
      ]
    },
    "unicode": {
      "supportsGridSearch": true
    }
  },
  "currentValue": "string",
  "defaultValue": "string",
  "parameterId": "string",
  "parameterName": "string",
  "taskName": "string",
  "vertexId": "string"
}

Properties

Name Type Required Restrictions Description
constraints Constraints true Constraints on valid values for this parameter. Note that any of these fields may be omitted but at least one will always be present. The presence of a field indicates that the parameter in question will accept values in the corresponding format.
currentValue any true The single value or list of values of the parameter that were grid searched. Depending on the grid search specification, could be a single fixed value (no grid search), a list of discrete values, or a range.

oneOf

Name Type Required Restrictions Description
» anonymous any false none

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 boolean false none

or

Name Type Required Restrictions Description
»» anonymous number false none

xor

Name Type Required Restrictions Description
» anonymous [anyOf] false none

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 boolean false none

or

Name Type Required Restrictions Description
»» anonymous number false none

continued

Name Type Required Restrictions Description
defaultValue any true The actual value used to train the model; either the single value of the parameter specified before training, or the best value from the list of grid-searched values (based on current_value).

oneOf

Name Type Required Restrictions Description
» anonymous any false none

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 boolean false none

or

Name Type Required Restrictions Description
»» anonymous number false none

xor

Name Type Required Restrictions Description
» anonymous [anyOf] false none

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 boolean false none

or

Name Type Required Restrictions Description
»» anonymous number false none

continued

Name Type Required Restrictions Description
parameterId string true Unique (per-blueprint) identifier of this parameter. This is the identifier used to specify which parameter to tune when make a new advanced tuning request.
parameterName string true Name of the parameter.
taskName string true Human-readable name of the task that this parameter belongs to.
vertexId string true Id of the vertex this parameter belongs to.

UploadRatingTable

{
  "parentModelId": "string",
  "ratingTableFile": "string",
  "ratingTableName": "string"
}

Properties

Name Type Required Restrictions Description
parentModelId string true the parent model this rating table file was derived from
ratingTableFile string(binary) true rating table file to use for the new rating table. Accepts Content-Type:multipart/form-data
ratingTableName string true the name of the new rating table to create

UseCaseDetails

{
  "createdAt": "string",
  "creatorEmail": "string",
  "creatorId": "string",
  "creatorName": "string",
  "id": "string",
  "name": "string"
}

Properties

Name Type Required Restrictions Description
createdAt string true Time when use-case was created
creatorEmail string¦null false Email of the user who created use-case
creatorId string true ID of the creator of the use-case
creatorName string¦null false Name of the user who created use-case
id string true ID of the associated use-case
name string¦null false Name of the use case at the moment of creation

UserMetadata

{
  "email": "string",
  "id": "string",
  "name": "string"
}

Properties

Name Type Required Restrictions Description
email string¦null true Email of the user
id string true ID of the user
name string¦null true Full name of the user

UserRoleWithGrant

{
  "canShare": true,
  "role": "ADMIN",
  "username": "string"
}

Properties

Name Type Required Restrictions Description
canShare boolean false Whether the org/group/user should be able to share with others.If true, the org/group/user will be able to grant any role up to and includingtheir own to other orgs/groups/user. If role is NO_ROLE canShare is ignored.
role string¦null true The role to set on the entity. When it is None, the role of this user will be removedfrom this entity.
username string true Username of the user to update the access role for.

Enumerated Values

Property Value
role [ADMIN, CONSUMER, DATA_SCIENTIST, EDITOR, OBSERVER, OWNER, READ_ONLY, READ_WRITE, USER]

Updated March 18, 2024