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Weighting variables in K-means clustering

Title
Weighting variables in K-means clustering
Authors
Huh M.-H.Lim Y.
Ewha Authors
임용빈
SCOPUS Author ID
임용빈scopus
Issue Date
2009
Journal Title
Journal of Applied Statistics
ISSN
0266-4763JCR Link
Citation
vol. 36, no. 1, pp. 67 - 78
Indexed
SCIE; SCOPUS WOS scopus
Abstract
The aim of this study is to assign weights w 1,..., wm to m clustering variables Z 1,..., Z m, so that k groups were uncovered to reveal more meaningful within-group coherence. We propose a new criterion to be minimized, which is the sum of the weighted within-cluster sums of squares and the penalty for the heterogeneity in variable weights w 1,..., w m. We will present the computing algorithm for such k-means clustering, a working procedure to determine a suitable value of penalty constant and numerical examples, among which one is simulated and the other two are real.
DOI
10.1080/02664760802382533
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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