D-optimality criterion for weighting variables in K-means clustering

DOI10.1016/j.jkss.2009.04.003zbMath1293.62136OpenAlexW2090571137MaRDI QIDQ2510893

Yeo Jung Park, Myung-Hoe Huh, Yong B. Lim

Publication date: 4 August 2014

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2009.04.003

zbMATH Keywords

variable weightingK-means clusteringD-optimality criterionWilks' lambda

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Response surface designs (62K20)

Uses Software

• LBFGS-B

Cites Work

• Unnamed Item
• Selection of variables in cluster analysis: An empirical comparison of eight procedures
• Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables
• Feature weighting in \(k\)-means clustering
• Optimal variable weighting for ultrametric and additive trees and \(K\)-means partitioning: Methods and software.
• Weighting variables in K-means clustering
• A Limited Memory Algorithm for Bound Constrained Optimization

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