1. A feature selection method used for a system including learning-pattern storage for storing and maintaining a learning pattern including class information, feature-candidate generation for generating a plurality of feature candidates, and feature decision for deciding a set of features suitable for pattern identification from among the plurality of feature candidates generated by the feature-candidate generation, wherein the feature decision decides a predetermined feature candidate having a largest amount of mutual information from the class information of the set of the learning patterns, as a first feature of the feature set, by calculating a feature value of each of the learning patterns corresponding to the feature candidates, predetermined feature candidates having a largest amount of mutual information from the class information of the set of the learning patterns under the condition that the decided features are known, as next features of the feature set, in sequence.