Domain knowledge-based evaluation of machine learning models

A system for analyzing machine learning models for domain knowledge-based evaluation of machine learning models for a target subject, comprising:

• a processor and a memory configured to provide computer program instructions to the processor to execute the function of code modules, the program instructions comprising:
• accessing a model explanation of each of a plurality of machine learning models for a target subject, wherein a model explanation includes a set of identified important features;
• receiving a domain expert input including a set of known important features for the target subject;
• comparing the domain expert input with the plurality of model explanations to evaluate consensus based on at least some of the known important features concurring with at least some of the identified important features of the model explanations;
• and
• scoring the machine learning models based on the evaluated consensus.

A computer program product for domain knowledge-based evaluation of machine learning models for a target subject, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

• access a model explanation of each of a plurality of machine learning models for a target subject, wherein a model explanation includes a set of identified important features;
• receive a domain expert input including a set of known important features for the target subject;
• compare the domain expert input with the plurality of model explanations to evaluate consensus based one at least some of the known important features concurring with at least some of the identified important features of the model explanations;
• and
• score the machine learning models based on the evaluated consensus.