Prototype based rules-a new way to understand the data

Abstract

Logical rules are not the only way to understand the structure of data. Prototype-based rules evaluate similarity to a small set of prototypes using optimized similarity measures. Such rules include crisp and fuzzy logic rules as special cases and are natural way of categorization from psychological point of view. An elimination procedure selecting good prototypes from a training set has been described. Illustrative applications on several datasets show that a few prototypes may indeed explain the data structure.