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DataRobot API resources > API reference documentation > DataRobot REST API > Mitigation > Challenger models

Mitigation Challenger Models

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

POST /api/v2/deployments/{deploymentId}/challengerPredictions/

Score main model prediction requests against challenger model requests.

Code samples

curl -X POST https://app.datarobot.com/api/v2/deployments/{deploymentId}/challengerPredictions/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter

{
  "timestamp": "2019-08-24T14:15:22Z"
}

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.
body body ChallengerScore false none

Responses

Status Meaning Description Schema
202 Accepted Job submitted. See Location header. None
422 Unprocessable Entity Unable to process the challenger scoring request. None
429 Too Many Requests Another challenger scoring job is running. See the Location header to track the running job. None

Response Headers

Status Header Type Format Description
202 Location string URL to poll to track challenger scoring progress.

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

BearerAuth

GET /api/v2/deployments/{deploymentId}/challengerReplaySettings/

Retrieve challenger replay settings.

Code samples

curl -X GET https://app.datarobot.com/api/v2/deployments/{deploymentId}/challengerReplaySettings/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.

Example responses

200 Response

{
  "enabled": true,
  "schedule": {
    "dayOfMonth": [
      "*"
    ],
    "dayOfWeek": [
      "*"
    ],
    "hour": [
      "*"
    ],
    "minute": [
      "*"
    ],
    "month": [
      "*"
    ]
  }
}

Responses

Status Meaning Description Schema
200 OK Challenger replay settings. ChallengersReplaySettings

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

BearerAuth

PATCH /api/v2/deployments/{deploymentId}/challengerReplaySettings/

Update challenger replay settings.

Code samples

curl -X PATCH https://app.datarobot.com/api/v2/deployments/{deploymentId}/challengerReplaySettings/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter

{
  "enabled": true,
  "schedule": {
    "dayOfMonth": [
      "*"
    ],
    "dayOfWeek": [
      "*"
    ],
    "hour": [
      "*"
    ],
    "minute": [
      "*"
    ],
    "month": [
      "*"
    ]
  }
}

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.
body body ChallengersReplaySettings false none

Responses

Status Meaning Description Schema
200 OK Challenger replay settings updated. None

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

BearerAuth

GET /api/v2/deployments/{deploymentId}/challengers/

List challenger models for deployment.

Code samples

curl -X GET https://app.datarobot.com/api/v2/deployments/{deploymentId}/challengers/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.

Example responses

200 Response

{
  "data": [
    {
      "id": "string",
      "model": {
        "datasetName": "string",
        "description": "string",
        "executionType": "string",
        "id": "string",
        "isDeprecated": true,
        "name": "string",
        "projectId": "string",
        "projectName": "string"
      },
      "modelPackage": {
        "id": "string",
        "name": "string",
        "registeredModelId": "string"
      },
      "name": "string",
      "predictionEnvironment": {
        "id": "string",
        "name": "string"
      }
    }
  ]
}

Responses

Status Meaning Description Schema
200 OK The challenger models ChallengerListResponse

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

BearerAuth

POST /api/v2/deployments/{deploymentId}/challengers/

Create new challenger model.

Code samples

curl -X POST https://app.datarobot.com/api/v2/deployments/{deploymentId}/challengers/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter

{
  "modelPackageId": "string",
  "name": "string",
  "predictionEnvironmentId": "string"
}

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.
body body ChallengerCreate false none

Responses

Status Meaning Description Schema
202 Accepted Job submitted successfully. See Location header. None
422 Unprocessable Entity Unable to process the challenger creation request. None

Response Headers

Status Header Type Format Description
202 Location string URL to poll to track challenger creation has finished.

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

BearerAuth

DELETE /api/v2/deployments/{deploymentId}/challengers/{challengerId}/

Delete challenger model.

Code samples

curl -X DELETE https://app.datarobot.com/api/v2/deployments/{deploymentId}/challengers/{challengerId}/ \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.
challengerId path string true Unique identifier of the challenger.

Responses

Status Meaning Description Schema
204 No Content Model successfully deleted. None

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

BearerAuth

GET /api/v2/deployments/{deploymentId}/challengers/{challengerId}/

Retrieve challenger model.

Code samples

curl -X GET https://app.datarobot.com/api/v2/deployments/{deploymentId}/challengers/{challengerId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.
challengerId path string true Unique identifier of the challenger.

Example responses

200 Response

{
  "id": "string",
  "model": {
    "datasetName": "string",
    "description": "string",
    "executionType": "string",
    "id": "string",
    "isDeprecated": true,
    "name": "string",
    "projectId": "string",
    "projectName": "string"
  },
  "modelPackage": {
    "id": "string",
    "name": "string",
    "registeredModelId": "string"
  },
  "name": "string",
  "predictionEnvironment": {
    "id": "string",
    "name": "string"
  }
}

Responses

Status Meaning Description Schema
200 OK The challenger model ChallengerResponse

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

BearerAuth

PATCH /api/v2/deployments/{deploymentId}/challengers/{challengerId}/

Update challenger model.

Code samples

curl -X PATCH https://app.datarobot.com/api/v2/deployments/{deploymentId}/challengers/{challengerId}/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter

{
  "name": "string",
  "predictionEnvironmentId": "string"
}

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.
challengerId path string true Unique identifier of the challenger.
body body ChallengerUpdate false none

Example responses

200 Response

{
  "id": "string",
  "model": {
    "datasetName": "string",
    "description": "string",
    "executionType": "string",
    "id": "string",
    "isDeprecated": true,
    "name": "string",
    "projectId": "string",
    "projectName": "string"
  },
  "modelPackage": {
    "id": "string",
    "name": "string",
    "registeredModelId": "string"
  },
  "name": "string",
  "predictionEnvironment": {
    "id": "string",
    "name": "string"
  }
}

Responses

Status Meaning Description Schema
200 OK Model successfully updated. ChallengerResponse

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

BearerAuth

GET /api/v2/deployments/{deploymentId}/championModelPackage/

Retrieve information about the champion model package

Code samples

curl -X GET https://app.datarobot.com/api/v2/deployments/{deploymentId}/championModelPackage/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name In Type Required Description
deploymentId path string true Unique identifier of the deployment.

Example responses

200 Response

{
  "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",
    "holdoutDataCreatedAt": "string",
    "holdoutDataCreatorEmail": "string",
    "holdoutDataCreatorId": null,
    "holdoutDataCreatorName": "string",
    "holdoutDatasetName": "string",
    "targetHistogramBaseline": "predictions",
    "trainingDataCatalogId": "string",
    "trainingDataCatalogVersionId": "string",
    "trainingDataCreatedAt": "string",
    "trainingDataCreatorEmail": "string",
    "trainingDataCreatorId": null,
    "trainingDataCreatorName": "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,
    "isFeatureDiscovery": true,
    "isMultiseries": true,
    "isTimeSeries": true,
    "isUnsupervisedLearning": true
  },
  "name": "string",
  "sourceMeta": {
    "customModelDetails": {
      "createdAt": "string",
      "creatorEmail": "string",
      "creatorId": "string",
      "creatorName": "string",
      "id": "string",
      "versionLabel": "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 Information retrieved successfully. ModelPackageRetrieveResponseBase

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

BearerAuth

Schemas

ChallengerCreate

{
  "modelPackageId": "string",
  "name": "string",
  "predictionEnvironmentId": "string"
}

Properties

Name Type Required Restrictions Description
modelPackageId string true ID of the model package to add as a challenger.
name string true maxLength: 512
 Human-readable name for the challenger.
predictionEnvironmentId string false ID of the Prediction Environment the challenger should use. If prediction environments are enabled, this is required

ChallengerListResponse

{
  "data": [
    {
      "id": "string",
      "model": {
        "datasetName": "string",
        "description": "string",
        "executionType": "string",
        "id": "string",
        "isDeprecated": true,
        "name": "string",
        "projectId": "string",
        "projectName": "string"
      },
      "modelPackage": {
        "id": "string",
        "name": "string",
        "registeredModelId": "string"
      },
      "name": "string",
      "predictionEnvironment": {
        "id": "string",
        "name": "string"
      }
    }
  ]
}

Properties

Name Type Required Restrictions Description
data [ChallengerResponse] true List of challengers.

ChallengerResponse

{
  "id": "string",
  "model": {
    "datasetName": "string",
    "description": "string",
    "executionType": "string",
    "id": "string",
    "isDeprecated": true,
    "name": "string",
    "projectId": "string",
    "projectName": "string"
  },
  "modelPackage": {
    "id": "string",
    "name": "string",
    "registeredModelId": "string"
  },
  "name": "string",
  "predictionEnvironment": {
    "id": "string",
    "name": "string"
  }
}

Properties

Name Type Required Restrictions Description
id string true ID of the challenger.
model ModelResponse true Model of the challenger.
modelPackage ModelPackageResponse true modelPackage of the challenger.
name string true Name of the challenger.
predictionEnvironment PredictionEnvironmentResponse false Prediction environment used by the challenger

ChallengerScore

{
  "timestamp": "2019-08-24T14:15:22Z"
}

Properties

Name Type Required Restrictions Description
timestamp string(date-time) false The date and time in ISO8601 format, challenger models will be scored on data starting from deployment creation until timestamp. If not specified UTC current time is used.

ChallengerUpdate

{
  "name": "string",
  "predictionEnvironmentId": "string"
}

Properties

Name Type Required Restrictions Description
name string false maxLength: 512
 Human-readable name for the challenger.
predictionEnvironmentId string false ID of the Prediction Environment the challenger should use.

ChallengersReplaySettings

{
  "enabled": true,
  "schedule": {
    "dayOfMonth": [
      "*"
    ],
    "dayOfWeek": [
      "*"
    ],
    "hour": [
      "*"
    ],
    "minute": [
      "*"
    ],
    "month": [
      "*"
    ]
  }
}

Properties

Name Type Required Restrictions Description
enabled boolean false Identifies whether scheduled replay is enabled.
schedule Schedule false The scheduling information defining how often and when to execute this job to the Job Scheduling service. Optional if enabled = False.

CustomModelDetails

{
  "createdAt": "string",
  "creatorEmail": "string",
  "creatorId": "string",
  "creatorName": "string",
  "id": "string",
  "versionLabel": "string"
}

Details of the custom model associated to this registered model version

Properties

Name Type Required Restrictions Description
createdAt string true Time when the custom model was created
creatorEmail string,null false Email of the user who created the custom model
creatorId string true ID of the creator of the custom model
creatorName string,null false Name of the user who created the custom model
id string true ID of the associated custom model
versionLabel string,null false Label of associated custom model version.

MlpkgFileContents

{
  "allTimeSeriesPredictionIntervals": true
}

Information about the content of .mlpkg artifact

Properties

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

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
}

Capabilities of the current model package.

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.

ModelPackageDatasets

{
  "baselineSegmentedBy": [
    "string"
  ],
  "datasetName": "string",
  "holdoutDataCatalogId": "string",
  "holdoutDataCatalogVersionId": "string",
  "holdoutDataCreatedAt": "string",
  "holdoutDataCreatorEmail": "string",
  "holdoutDataCreatorId": null,
  "holdoutDataCreatorName": "string",
  "holdoutDatasetName": "string",
  "targetHistogramBaseline": "predictions",
  "trainingDataCatalogId": "string",
  "trainingDataCatalogVersionId": "string",
  "trainingDataCreatedAt": "string",
  "trainingDataCreatorEmail": "string",
  "trainingDataCreatorId": null,
  "trainingDataCreatorName": "string",
  "trainingDataSize": 0
}

dataset information for the model package

Properties

Name Type Required Restrictions Description
baselineSegmentedBy [string] 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)
holdoutDataCreatedAt string,null false Time when the holdout data item was created
holdoutDataCreatorEmail string,null false Email of the user who created the holdout data item
holdoutDataCreatorId string,null false ID of the creator of the holdout data item
holdoutDataCreatorName string,null false Name of the user who created the holdout data item
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)
trainingDataCreatedAt string,null false Time when the training data item was created
trainingDataCreatorEmail string,null false Email of the user who created the training data item
trainingDataCreatorId string,null false ID of the creator of the training data item
trainingDataCreatorName string,null false Name of the user who created the training data item
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"
}

Information from when this Model Package was first saved

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

ModelPackageModelDescription

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

model description information for the model package

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,
  "isFeatureDiscovery": true,
  "isMultiseries": true,
  "isTimeSeries": true,
  "isUnsupervisedLearning": true
}

Model attribute information

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
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

ModelPackageResponse

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

modelPackage of the challenger.

Properties

Name Type Required Restrictions Description
id string true ID of the model package.
name string true Type of the current model.
registeredModelId string,null false ID of the associated registered model

ModelPackageRetrieveResponseBase

{
  "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",
    "holdoutDataCreatedAt": "string",
    "holdoutDataCreatorEmail": "string",
    "holdoutDataCreatorId": null,
    "holdoutDataCreatorName": "string",
    "holdoutDatasetName": "string",
    "targetHistogramBaseline": "predictions",
    "trainingDataCatalogId": "string",
    "trainingDataCatalogVersionId": "string",
    "trainingDataCreatedAt": "string",
    "trainingDataCreatorEmail": "string",
    "trainingDataCreatorId": null,
    "trainingDataCreatorName": "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,
    "isFeatureDiscovery": true,
    "isMultiseries": true,
    "isTimeSeries": true,
    "isUnsupervisedLearning": true
  },
  "name": "string",
  "sourceMeta": {
    "customModelDetails": {
      "createdAt": "string",
      "creatorEmail": "string",
      "creatorId": "string",
      "creatorName": "string",
      "id": "string",
      "versionLabel": "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
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
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"
}

If available, information about the model's scoring code

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

{
  "customModelDetails": {
    "createdAt": "string",
    "creatorEmail": "string",
    "creatorId": "string",
    "creatorName": "string",
    "id": "string",
    "versionLabel": "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"
  }
}

Meta information from where this model was generated

Properties

Name Type Required Restrictions Description
customModelDetails CustomModelDetails false Details of the custom model associated to this registered model version
environmentUrl string,null(uri) 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"
}

target information for the model package

Properties

Name Type Required Restrictions Description
classCount integer,null true minimum: 0
 Number of classes for classification models.
classNames [string] 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, GeoPoint]

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"
}

time series information for the model package

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] 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]

ModelResponse

{
  "datasetName": "string",
  "description": "string",
  "executionType": "string",
  "id": "string",
  "isDeprecated": true,
  "name": "string",
  "projectId": "string",
  "projectName": "string"
}

Model of the challenger.

Properties

Name Type Required Restrictions Description
datasetName string true Name of dataset used to train challenger model
description string true Description of the model.
executionType string true Type of the current model.
id string true ID of the current model.
isDeprecated boolean true Whether the current model is deprecated model. eg. python2 based model.
name string true Name of the model.
projectId string true Project ID of the current model.
projectName string true Project name of the current model.

PredictionEnvironmentResponse

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

Prediction environment used by the challenger

Properties

Name Type Required Restrictions Description
id string true ID of the prediction environment.
name string true Name of the prediction environment.

Schedule

{
  "dayOfMonth": [
    "*"
  ],
  "dayOfWeek": [
    "*"
  ],
  "hour": [
    "*"
  ],
  "minute": [
    "*"
  ],
  "month": [
    "*"
  ]
}

The scheduling information defining how often and when to execute this job to the Job Scheduling service. Optional if enabled = False.

Properties

Name Type Required Restrictions Description
dayOfMonth [number,string] true maxItems: 31
 The date(s) of the month that the job will run. Allowed values are either [1 ... 31] or ["*"] for all days of the month. This field is additive with dayOfWeek, meaning the job will run both on the date(s) defined in this field and the day specified by dayOfWeek (for example, dates 1st, 2nd, 3rd, plus every Tuesday). If dayOfMonth is set to ["*"] and dayOfWeek is defined, the scheduler will trigger on every day of the month that matches dayOfWeek (for example, Tuesday the 2nd, 9th, 16th, 23rd, 30th). Invalid dates such as February 31st are ignored.
dayOfWeek [number,string] true maxItems: 7
 The day(s) of the week that the job will run. Allowed values are [0 .. 6], where (Sunday=0), or ["*"], for all days of the week. Strings, either 3-letter abbreviations or the full name of the day, can be used interchangeably (e.g., "sunday", "Sunday", "sun", or "Sun", all map to [0]. This field is additive with dayOfMonth, meaning the job will run both on the date specified by dayOfMonth and the day defined in this field.
hour [number,string] true maxItems: 24
 The hour(s) of the day that the job will run. Allowed values are either ["*"] meaning every hour of the day or [0 ... 23].
minute [number,string] true maxItems: 60
 The minute(s) of the day that the job will run. Allowed values are either ["*"] meaning every minute of the day or[0 ... 59].
month [number,string] true maxItems: 12
 The month(s) of the year that the job will run. Allowed values are either [1 ... 12] or ["*"] for all months of the year. Strings, either 3-letter abbreviations or the full name of the month, can be used interchangeably (e.g., "jan" or "october"). Months that are not compatible with dayOfMonth are ignored, for example {"dayOfMonth": [31], "month":["feb"]}.

UseCaseDetails

{
  "createdAt": "string",
  "creatorEmail": "string",
  "creatorId": "string",
  "creatorName": "string",
  "id": "string",
  "name": "string"
}

Details of the use-case associated to this registered model version

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"
}

Information on the user who last modified the registered model

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
Updated March 25, 2025