WeDIV – An improved k-means clustering algorithm with a weighted distance and a novel internal validation index

Designing appropriate similarity metrics (distance) and estimating the optimal number of clusters have been two important issues in cluster analysis. This study proposed an improved k-means clustering algorithm involving a Weighted Distance and a novel Internal Validation index (WeDIV). The weighted...

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Vydané v:	Egyptian informatics journal Ročník 23; číslo 4; s. 133 - 144
Hlavní autori:	Ning, Zilan, Chen, Jin, Huang, Jianjun, Sabo, Umar Jlbrilla, Yuan, Zheming, Dai, Zhijun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.12.2022 Elsevier
Predmet:	Clustering EP_dis formula omitted Internal validation index RCH Weighted distance EP_dis Internal validation index Weighted distance Clustering RCH
ISSN:	1110-8665, 2090-4754
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