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DataRobot Tools

Datarobot Create Batch Monitoring

Tool to create a DataRobot Batch Monitoring job for tracking model performance and data drift on batch predictions. Use when you need to monitor predictions at scale. The job is created asynchronously and returns immediately with a job ID.

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Use Datarobot Create Batch Monitoring

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Inputs

  • modelIdstring
    ID of leaderboard model which is used for processing predictions dataset.
  • chunkSize
    Strategy for determining chunk size. Can be "auto", "fixed", "dynamic", or a fixed size in bytes.
  • csvSettingsobject
    Required
    CSV settings for intake and output files.
  • abortOnErrorboolean
    Should this job abort if too many errors are encountered.
  • batchJobTypestring
    Batch job type enumeration
  • deploymentIdstring
    Required
    ID of deployment which is used in job for processing predictions dataset. Use LIST_DEPLOYMENTS to find available deployments.
  • thresholdLownumber
    Compute explanations for predictions below this threshold.
  • numConcurrentinteger
    Number of simultaneous requests to run against the prediction instance.
  • pinnedModelIdstring
    Specify a model ID used for scoring.
  • thresholdHighnumber
    Compute explanations for predictions above this threshold.
  • intakeSettingsobject
    Required
    Intake option for the job. Must include "type" field. Example for HTTP: {"type": "http", "url": "https://example.com/test.csv"}. Example for local file: {"type": "localFile"}.
  • modelPackageIdstring
    ID of model package from registry used for processing predictions dataset.

Observable output

  • data
    Required
    Data from the action execution
  • errorstring
    Error if any occurred during the execution of the action
  • successfulboolean
    Required
    Whether or not the action execution was successful or not

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