Detecting suitability of machine learning models for datasets

A method comprising:

• calculating a first statistical data signature for a training data set of a machine learning system using one or more predefined statistical algorithms, the training data set used to generate a machine learning model;
• calculating a second statistical data signature for an inference data set of the machine learning system using the one or more predefined statistical algorithms, the inference data set analyzed using the machine learning model;
• calculating a suitability score describing the suitability of the training data set to the inference data set as a function of the first and the second statistical data signatures;
• and
• performing an action related to the machine learning system in response to the suitability score satisfying an unsuitability threshold.

An apparatus comprising:

• means for calculating a first statistical data signature for a training data set of a machine learning system using one or more predefined statistical algorithms, the training data set used to generate a machine learning model;
• means for calculating a second statistical data signature for an inference data set of the machine learning system using the one or more predefined statistical algorithms, the inference data set analyzed using the machine learning model;
• means for calculating a suitability score describing the suitability of the training data set to the inference data set as a function of the first and the second statistical data signatures;
• and
• means for performing an action related to the machine learning system in response to the suitability score satisfying an unsuitability threshold.