Even-sized clustering based on noise clustering

Abstract

Clustering is a method of data analysis without the use of supervised data. Even-sized clustering based on optimization (ECBO) is a clustering algorithm that focuses on cluster size with the constraints that cluster sizes must be the same. However, ECBO has the problem that it is susceptible to noise. It is believed that this issue can be overcome by applying noise clustering method. Noise clustering is a method that makes noise less susceptible to noise by classifying it into noise clusters by identifying noise. In this paper, we propose a new even-sized clustering algorithm based on noise clustering and verify its effectiveness through numerical examples.