Homogeneity Separateness: A New Validity Measure for Clustering Problems

  • M. Ramakrishna Murty
  • J. V. R. Murthy
  • P. V. G. D. Prasad Reddy
  • Anima Naik
  • Suresh. C. Satapathy
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 248)


Several validity indices have been designed to evaluate solutions obtained by clustering algorithms. Traditional indices are generally designed to evaluate center-based clustering, where clusters are assumed to be of globular shapes with defined centers or representatives. Therefore they are not suitable to evaluate clusters of arbitrary shapes, sizes and densities, where clusters have no defined centers or representatives. In this work, HS (Homogeneity Separateness) validity measure based on a different shape is proposed. It is suitable for clusters of any shapes, sizes and/or of different densities. The main concepts of the proposed measure are explained and experimental results on both synthetic and real life data set that support the proposed measure are given.


Cluster validity index homogeneity separateness spanning tree CS Measure 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • M. Ramakrishna Murty
    • 1
  • J. V. R. Murthy
    • 2
  • P. V. G. D. Prasad Reddy
    • 3
  • Anima Naik
    • 4
  • Suresh. C. Satapathy
    • 5
  1. 1.Dept. of CSEGMR Institute of TechnologyRajamIndia
  2. 2.Dept. of CSEJNTUKKakinadaIndia
  3. 3.Dept. of CS&SEAndhra UniversityVisakhapatnamIndia
  4. 4.Majhighariani Institute of Technology and SciencesRayagadaIndia
  5. 5.Dept. of CSEANITSVisakhapatnaIndia

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