An efficient k′-means clustering algorithm

This paper introduces k′-means algorithm that performs correct clustering without pre-assigning the exact number of clusters. This is achieved by minimizing a suggested cost-function. The cost-function extends the mean-square-error cost-function of k-means. The algorithm consists of two separate ste...

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Veröffentlicht in:	Pattern recognition letters Jg. 29; H. 9; S. 1385 - 1391
1. Verfasser:	Žalik, Krista Rizman
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.07.2008 Elsevier
Schlagworte:	Applied sciences Cluster number Clustering analysis Cost-function Exact sciences and technology Information, signal and communications theory k-Means Rival penalized Signal and communications theory Signal representation. Spectral analysis Signal, noise Telecommunications and information theory Clustering analysis Rival penalized Cluster number Cost-function k-Means Cluster analysis Performance evaluation Cost minimization Automatic classification Iterative method K means algorithm Signal classification Mean square error Cost function
ISSN:	0167-8655, 1872-7344
Online-Zugang:	Volltext
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