Improved rough k-means clustering algorithm based on weighted distance measure with Gaussian function

Rough k-means clustering algorithm and its extensions are introduced and successfully applied to real-life data where clusters do not necessarily have crisp boundaries. Experiments with the rough k-means clustering algorithm have shown that it provides a reasonable set of lower and upper bounds for...

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Vydané v:	International journal of computer mathematics Ročník 94; číslo 4; s. 663 - 675
Hlavní autori:	Zhang, Tengfei, Ma, Fumin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Taylor & Francis 03.04.2017 Taylor & Francis Ltd
Predmet:	Algorithms Approximation Cluster analysis Clustering Clustering algorithm Clusters Computer simulation Gaussian function Mathematical analysis Mathematical models rough k-means rough set theory Routing Vector quantization weighted distance measure
ISSN:	0020-7160, 1029-0265
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