A novel validity measure for clusters of arbitrary shapes and densities

Noha Yousri, Mohamed S. Kamel, Mohamed A. Ismail

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

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 and densities, where clusters have no defined centers or representatives, but formed based on the connectivity of patterns to their neighbours. In this work, a novel validity measure based on a density-based criterion is proposed. It is based on the concept that densities of clusters can be distinguished by the neighbourhood distances between patterns. It is suitable for clusters of any shapes and of different densities. The main concepts of the proposed measure are explained and experimental results that support the proposed measure are given.

Original languageEnglish
Title of host publication2008 19th International Conference on Pattern Recognition, ICPR 2008
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event2008 19th International Conference on Pattern Recognition, ICPR 2008 - Tampa, FL, United States
Duration: 8 Dec 200811 Dec 2008

Other

Other2008 19th International Conference on Pattern Recognition, ICPR 2008
CountryUnited States
CityTampa, FL
Period8/12/0811/12/08

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Yousri, N., Kamel, M. S., & Ismail, M. A. (2008). A novel validity measure for clusters of arbitrary shapes and densities. In 2008 19th International Conference on Pattern Recognition, ICPR 2008 [4761242]