STATISTICAL MODEL LEARNING DEVICE, METHOD, AND PROGRAM

摘要

It is possible to provide a statistical model learning device which can calculate a prediction distribution considering affects of the state density while avoiding the problem of a statistical amount attributed to model parameter integration. The statistical model learning device includes: self-response function calculation means (102) which calculates a self-response function of a model parameter; eigenvalue analysis means (103) which calculates eigenvalues and eigenvectors of a matrix having self-response functions between M model parameters as components; and prediction distribution calculation means (104) which calculates a weight of a model parameter by using values of M' eigenvalues and values of eigenvectors corresponding to M' which is smaller than M in the descending order of the eigenvalues among the eigenvalues and the eigenvectors calculated by the eigenvalue analysis means (103), and calculates a prediction distribution as a weighted sum, assuming that the model parameter has the weight.