Nonsupervised classification using the principal component

摘要

This paper presents a mathematical model of a nonsupervised two-category classifier with a nonparametric learning method by using the first principal component. On the assumptions that the patterns of each category are clustered and that the mean point of all patterns used lies between the two clusters, the separating hyperplane contains the mean pattern point and is perpendicular to the line governed by the first principal component. The learning algorithm for obtaining the mean pattern vector and the first principal component is described, and also some experimental results on random patterns are presented.