Analysis-data analyzing device and analysis-data analyzing method that calculates or updates a degree of usefulness of each dimension of an input in a machine-learning model

Abstract

Using training data, machine learning is performed to construct a learning model which is a non-linear function for discrimination or regression analysis (S). A degree of contribution of each input dimension is calculated from a partial differential value of that function. Input dimensions to be invalidated are determined using a threshold defined by a Gaussian distribution function based on the degrees of contribution (S-S). Machine learning is once more performed using the training data with the partially-invalidated input dimensions (S). A new value of the degree of contribution of each input dimension is determined from the obtained learning model, and the degree of contribution is updated using the old and new values (S-S). After the processes of Steps S-Sare iterated a specified number of times (S), useful dimensions are determined based on the finally obtained degrees of contribution, and the machine-learning model is constructed (S).