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datadriftdetector Module

  • Reference

Contains core functionality for detecting data drift between two datasets in Azure Machine Learning.

Data drift is measured through datasets or deployments, and relies on the Dataset API.

Classes

DataDriftDetector

Defines a data drift monitor that can be used to run data drift jobs in Azure Machine Learning.

The DataDriftDetector class enables you to identify drift between a given baseline and target dataset. A DataDriftDetector object is created in a workspace by either specifying the baseline and target datasets directly. For more information, see https://aka.ms/datadrift.

Datadriftdetector constructor.

The DataDriftDetector constructor is used to retrieve a cloud representation of a DataDriftDetector object associated with the provided workspace.