Machine learning device, machine learning method, and program

Abstract

A machine learning device according to one embodiment of the present invention is provided with a storage unit and a processor. The storage unit stores answer data including: parameters presented in relation to measurement of a psychological measurement function; and answer results for the parameters from users. The processor is provided with an evaluation function application unit, a model training unit, a parameter selection unit, and a parameter presentation unit. The evaluation function application unit acquires evaluation values by applying an evaluation function to the answer results. The model training unit repeatedly feeds the parameters and the evaluation values of the answer data into a machine learning model to cause the same to learn through machine learning, thereby generating a trained model corresponding to the psychological measurement function. The parameter selection unit selects the parameters to be presented by Bayesian optimization based on the evaluation values and the trained model. The parameter presentation unit presents the selected parameters to subject users.