Fast global \(k\)-means clustering based on local geometrical information

DOI10.1016/j.ins.2013.05.023zbMath1321.62066OpenAlexW2155042468MaRDI QIDQ497555

Chao Sui, Chuangyin Dang, Liang Bai, J. Y. Liang

Publication date: 24 September 2015

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2013.05.023

zbMATH Keywords

optimizationcomputational complexitycluster analysisglobal \( k\)-means clusteringlocal geometrical information

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems, Responsive threshold search based memetic algorithm for balanced minimum sum-of-squares clustering, Global optimality in \(k\)-means clustering, Initialization of \(K\)-modes clustering using outlier detection techniques, A novel fast heuristic to handle large-scale shape clustering

Uses Software

• UCI-ml

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Clustering and selecting suppliers based on simulated annealing algorithms
• Fast modified global \(k\)-means algorithm for incremental cluster construction
• \(K\)-harmonic means data clustering with simulated annealing heuristic
• Modified global \(k\)-means algorithm for minimum sum-of-squares clustering problems
• Fast global \(k\)-means clustering using cluster membership and inequality
• A new measure of uncertainty based on knowledge granulation for rough sets
• MGRS: a multi-granulation rough set
• A near-optimal initial seed value selection in K-means means algorithm using a genetic algorithm