Applying Rough Set Concepts to Clustering

摘要: Clustering algorithms are probably the most commonly used methods in data mining. Applications can be found virtually any domain; prominent areas of application e.g. bioinformatics, engineering and marketing besides many others. In applications classic k-means clustering algorithm is applied. Its fuzzy version, Bezdek’s c-means has also gained tremendous attention. Another soft computing based on rough set been recently introduced by Lingras. This chapter describes how a core concept sets, lower upper approximation set, clustering. Rough clusters shown to useful for representing groups highway sections, web users, supermarket customers.