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Knowledge and Information Systems
Erschienen in: Knowledge and Information Systems 3/2014

01.09.2014 | Regular Paper

Integration of artificial immune network and K-means for cluster analysis

verfasst von: R. J. Kuo, S. S. Chen, W. C. Cheng, C. Y. Tsai

Erschienen in: Knowledge and Information Systems | Ausgabe 3/2014

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Abstract

This study is dedicated to propose a cluster analysis algorithm which is integration of artificial immune network (aiNet) and K-means algorithm (aiNetK). Four benchmark data sets, Iris, Wine, Glass, and Breast Cancer, are employed to testify the proposed algorithm. The computational results reveal that aiNetK is superior to particle swam optimization and artificial immune system-related methods.
Vorheriger Artikel Efficient clustering of uncertain data streams
Nächster Artikel Introducing semantic variables in mixed distance measures: Impact on hierarchical clustering

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Metadaten
Titel
Integration of artificial immune network and K-means for cluster analysis
verfasst von
R. J. Kuo
S. S. Chen
W. C. Cheng
C. Y. Tsai
Publikationsdatum
01.09.2014
Verlag
Springer London
Erschienen in
Knowledge and Information Systems / Ausgabe 3/2014
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-013-0649-3

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