Nonparametric genetic clustering: comparison of validity indices

Author

Bandyopadhyay, Sanghamitra ; Maulik, Ujjwal

Author_Institution

Machine Intelligence Unit, Indian Stat. Inst., Calcutta, India

Volume

31

Issue

1

fYear

2001

fDate

2/1/2001 12:00:00 AM

Firstpage

120

Lastpage

125

Abstract

A variable-string-length genetic algorithm (GA) is used for developing a novel nonparametric clustering technique when the number of clusters is not fixed a-priori. Chromosomes in the same population may now have different lengths since they encode different number of clusters. The crossover operator is redefined to tackle the concept of variable string length. A cluster validity index is used as a measure of the fitness of a chromosome. The performance of several cluster validity indices, namely the Davies-Bouldin (1979) index, Dunn´s (1973) index, two of its generalized versions and a recently developed index, in appropriately partitioning a data set, are compared

Keywords

genetic algorithms; mathematical operators; nonparametric statistics; pattern clustering; performance index; Davies-Bouldin index; Dunn index; chromosome fitness; cluster encoding; cluster validity indices; crossover operator; data set partitioning; generalized versions; genetic algorithm; nonparametric genetic clustering; pattern recognition; performance; variable string length; Biological cells; Biological information theory; Computer science; Evolution (biology); Genetic algorithms; Genetic mutations; Machine intelligence; Parallel processing; Pattern classification; Pattern recognition;

fLanguage

English

Journal_Title

Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on

Publisher

ieee

ISSN

1094-6977

Type

jour

DOI

10.1109/5326.923275

Filename

923275