Bias adjustment device, information processing device, information processing method, and information processing program

Abstract

A bias adjustment device uses an identification model developed by machine learning using training data, and includes a calculation unit that calculates first identification accuracy of the identification model trained on first training data and second identification accuracy of the identification model trained on second training data acquired by an adjustment of the number of pieces of data of the first training data, a prediction unit that predicts a change in identification accuracy with respect to the number of pieces of training data on the basis of the first identification accuracy and the second identification accuracy, and a control unit that adjusts the number of pieces of data used for the training or changes the identification model, on the basis of the predicted change in the identification accuracy, in such a manner that the predicted change in the identification accuracy becomes a predetermined target value.