Variable selection method, variable selection program and variable selection system

摘要

PROBLEM TO BE SOLVED: To provide a variable selection method for machine learning capable of improving prediction accuracy and the like. The present invention is a variable selection method for selecting a specific variable group used for machine learning from all variable groups constituting a target population data group. In the variable selection method, the mutual information amount of the variable pair, which is a combination of one or more first variables extracted from all variable groups and each second variable extracted from all variable groups unlike the first variable, is used as the mother data. The information amount calculation step calculated using the group and the selection variable group consisting of the second variable or the variable pair extracted by a predetermined number of selections in descending order from the one with the largest mutual information amount are selected from the population data group. It includes a verification step for creating a learning model and evaluating performance using the selection data group related to the variable group. The specific variable group is selected based on the relationship between the number of selections of the selection variable group and the performance of the learning model. [Selection diagram] Fig. 5