Data model processing in machine learning using a reduced set of features

A computer system for training a predictive model, the computer system comprising:

• one or more computer processors;
• one or more computer readable storage media;
• program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising instructions to:
• select, from a dataset comprising a plurality of cases and controls and a plurality of features, a plurality of subsets of features;
• match cases and controls to select a plurality of case-control subsets for each subset of features, each case-control subset having similar values for the corresponding subset of features;
• identify, for each case-control subset, a statistical significance of each feature of the plurality of features absent from the subset of features used to match the case-control subset;
• select a final subset of features based on the statistical significance of each feature for the plurality of case-control subsets;
• and
• train a predictive model using the final subset of features.

A computer program product for training a predictive model, the computer program product comprising one or more computer readable storage media collectively having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to:

• select, from a dataset comprising a plurality of cases and controls and a plurality of features, a plurality of subsets of features;
• match cases and controls to select a plurality of case-control subsets for each subset of features, each case-control subset having similar values for the corresponding subset of features;
• identify, for each case-control subset, a statistical significance of each feature of the plurality of features absent from the subset of features used to match the case-control subset;
• select a final subset of features based on the statistical significance of each feature for the plurality of case-control subsets;
• and
• train a predictive model using the final subset of features.