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Databricks Ml Experiments Create Run

Tool to create a new MLflow run within an experiment for tracking machine learning execution. Use when starting a new ML training run, experiment execution, or data pipeline that needs parameter and metric tracking. Returns the created run with a unique run_id for subsequent met…

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Use Databricks Ml Experiments Create Run

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Free
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Not currently supported

Inputs

  • tagsarray
    Additional metadata for the run as key-value pairs. Tags can be used to categorize, filter, and organize runs.
  • user_idstring
    ID of the user executing the run. This field is deprecated as of MLflow 1.0 and should not be used in new implementations.
  • run_namestring
    Name assigned to the run. This is a human-readable identifier for the run.
  • start_timeinteger
    Unix timestamp in milliseconds of when the run started. If not provided, the current time will be used.
  • experiment_idstring
    The associated experiment identifier. This is the ID of the experiment under which the run will be created.

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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