Prototypes selection based on similarity relations for classification problems

Abstract

In this paper, a new method for solving classification problems based on prototypes is proposed. When using similarity relations for the granulation of the universe, similarity classes are generated and a prototypes is selected for each similarity class. Experimental results showing the performance of our method and comparing accuracy against other prototype selection methods reported.