Clustering based-on indiscernibility and indiscernibility level

Abstract

The core concept of classical rough sets are clustering similarities and dissimilarities of objects based on the notions of indiscernibility and discernibility. In this paper, we present a new method of clustering data based on the combination of indiscernibility and its indiscernibility level. The indiscernibility level quantifies the indiscernibility of pairs of objects among other objects in information systems. The result of this paper show the dual notions of indiscernibility and its indiscernibility level play an important role in clustering information systems.