Evolutionary and Iterative Crisp and Rough Clustering I: Theory

  • Manish Joshi
  • Pawan Lingras
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5909)

Abstract

Researchers have proposed several Genetic Algorithms (GA) based clustering algorithms for crisp and rough clustering. In this two part series of papers, we compare the effect of GA optimization on resulting cluster quality of K-means, GA K-means, rough K-means, GA rough K-means and GA rough K-medoid algorithms. In this first part, we present the theoretical foundation of the transformation of the crisp clustering K-means and K-medoid algorithms into rough and evolutionary clustering algorithms. The second part of the paper will present experiments with a real world data set, and a standard data set.

Keywords

Crisp Clustering Rough Clustering GA Rough K-means GA Rough K-medoid 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Manish Joshi
    • 1
  • Pawan Lingras
    • 2
  1. 1.Department of Computer ScienceNorth Maharashtra UniversityJalgaonIndia
  2. 2.Department of Mathematics and Computing ScienceSaint Mary’s UniversityHalifaxCanada

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