A classifier learning apparatus (100) includes: an object acquisition unit (101) that acquires a set of reference vectors and assigned category information of the respective reference vectors as a processing object; a specifying unit (102) that specifies an internal nearest neighbor reference vector nearest to a sample vector among the reference vectors assigned to the same category as the sample vector and specifies an external nearest neighbor reference vector nearest to the sample vector among the reference vectors assigned to a category different from that of the sample vector; a calculation unit (103) that calculates an evaluation value of the processing object using a distance between the sample vector and a classification boundary formed by the internal nearest neighbor reference vector and the external nearest neighbor reference vector; and an updating unit (104) that updates an original set of reference vectors and original assigned category information with the processing object based on the evaluation value.