Machine learning entity validation performance reporting

Abstract

The present disclosure is generally related to artificial intelligence (AI) and/or machine learning (ML) workflows including ML entity lifecycle management and reporting mechanisms for reporting the validation performance of an ML entity. An ML training (MLT) function trains an ML model using a training dataset and may validate the ML model using a validation dataset. An MLT report is generated, which includes an attribute indicating the performance of the ML model when performing on training data. To support the ML model validation performance reporting, an attribute is defined in the MLT report to indicate the performance of the ML model when performing on the validation data. The attribute may be a new attribute or an extension/enhancement of an existing attribute in the MLT training report.