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
Cluster analysisCrossoverNonparametric statisticsMathematicsIndex (typography)Variable (mathematics)PopulationStatisticsSet (abstract data type)String (physics)Data miningComputer scienceArtificial intelligence
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Publication Info
- Year
- 2001
- Type
- article
- Volume
- 31
- Issue
- 1
- Pages
- 120-125
- Citations
- 265
- Access
- Closed
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Cite This
Sanghamitra Bandyopadhyay,
Ujjwal Maulik
(2001).
Nonparametric genetic clustering: comparison of validity indices.
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
, 31
(1)
, 120-125.
https://doi.org/10.1109/5326.923275
Identifiers
- DOI
- 10.1109/5326.923275