The K-Modes Method under Possibilistic Framework

摘要

In this paper, we develop a new clustering method combining the possibility theory with the standard k-modes method (SKM). The proposed method is called KM-PF to express the fact that it is a modification of k-modes algorithm under possibilistic framework. KM-PM incorporates possibilistic theory in two distinct stages in application of the SKM combining the possibilistic k-modes (PKM) and the k-modes using possibilistic membership (KM-PM). First, it deals with uncertain attribute values of instances using possibilistic distributions. Then, it computes the possibilistic membership degrees of each object to all clusters. Experimental results show that the proposed method compares favourably to the SKM, PKM and KM-PM.