An Extension of the Traditional Classication Rules: the Case of Non-Random Samples

Abstract

The paper deals with an heuristic generalization of the traditional classication rules by incorporating within sample dependencies. The main motivation behind this generalization is to develop a new classication rule when training samples are not random, but, jointly equicorrelated.Classication rules; Non-random samples; Jointly equicorrelated training vectors