Machine learning model evaluation and comparison

Abstract

Disclosed are systems and methods to compare two or more machine learning models to determine the comparative performance of those models. Markers may be assigned to data items and data item marker scores generated for those data items, independent of the machine learning models. Each of the machine learning models to be compared may then process the data items and generate respective model scores for those data items. A sub-set of the data items may then be generated for each machine learning model based on the model scores assigned to the data items by the respective model. A model marker score may then be computed for each machine learning model based on the marker scores assigned to each of the data items of the sub-set of data items determined for each model. Finally, the model marker scores may be compared to determine which machine learning model has the highest performance.