Clustering stability-based evolutionary K-means

DOI10.1007/s00500-018-3280-0OpenAlexW2805339146MaRDI QIDQ2001129

Zhenfeng He, ChunYan Yu

Publication date: 2 July 2019

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-018-3280-0

zbMATH Keywords

clusteringgenetic algorithmconsensus clusteringK-Means algorithmclustering stability

Mathematics Subject Classification ID

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

Related Items (2)

\(k\)-means genetic algorithms with greedy genetic operators ⋮ Genetic Algorithms with the Crossover-Like Mutation Operator for the k-Means Problem

Uses Software

• R
• CLUES
• Silhouettes
• UCI-ml
• MOCK
• NbClust
• k-means++

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• A bad instance for \texttt{k-means++}
• Selection of the number of clusters via the bootstrap method
• Cluster-wise assessment of cluster stability
• CLUES: a non-parametric clustering method based on local shrinking
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• Consensus clustering: A resampling-based method for class discovery and visualization of gene expression microarray data
• An evolutionary technique based on K-means algorithm for optimal clustering in \({\mathbb R}^{N}\)
• Stability and model selection in \(k\)-means clustering
• A Survey of Statistical Network Models
• How the initialization affects the stability of the қ-means algorithm
• A Sober Look at Clustering Stability

This page was built for publication: Clustering stability-based evolutionary K-means