Nonparametric genetic clustering: Comparison of validity indices

被引:184
作者
Bandyopadhyay, S [1 ]
Maulik, U
机构
[1] Indian Stat Inst, Machine Intelligence Unit, Kolkata 700035, W Bengal, India
[2] Kalyani Govt Engn Coll, Dept Comp Sci & Technol, Kalyani, W Bengal, India
来源
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS | 2001年 / 31卷 / 01期
关键词
clustering; cluster validity; Davies-Bouldin (DB) index; generalized Dunn's index; genetic algorithms (GAs); pattern recognition;
D O I
10.1109/5326.923275
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. Cluster validity index is used as a measure of the fitness of a chromosome. The performance of several cluster validity indices, namely, Davies-Bouldin (DB) index, Dunn's index, two of its generalized versions and a recently developed index, in appropriately partitioning a data set, are compared.
引用
收藏
页码:120 / 125
页数:6
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