MO − Mineclust: A framework for multi-objective clustering

Abstract

This article presents MO − Mineclust a first package of the platform in development MO − Mine. This platform aims at providing optimization algorithms, and in particular multi-objective approaches, to deal with classical datamining tasks (Classification, association rules…). This package MO − Mineclust is dedicated to clustering. Indeed, it is well-known that clustering may be seen as a multi-objective optimization problem as the goal is both to minimize distances between data belonging to a same cluster, while maximizing distances between data belonging to different clusters. In this paper we present the framework as well as experimental results, to attest the benefit of using multi-objective approaches for clustering.