Rough classification based on correlation clustering

Abstract

In this article we propose a two-step classification method. At the first step it constructs a tolerance relation from the data, and at second step it uses correlation clustering to construct the base sets, which are used at the classification of the objects. Besides the exposition of the theoretical background we also show this method in action: we present the details of the classification of the well-known iris data set. Moreover we frame some open question due this kind of classification.