On the number of groups in clustering

DOI10.1016/j.spl.2011.07.005zbMath1225.62083OpenAlexW1969616714MaRDI QIDQ645416

Aurélie Fischer

Publication date: 15 November 2011

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2011.07.005

zbMATH Keywords

model selectionoracle inequality\(k\)-means clusteringnumber of clustersslope heuristics

Mathematics Subject Classification ID

Related Items (7)

Some theoretical results regarding the polygonal distribution ⋮ Clustering transformed compositional data usingK-means, with applications in gene expression and bicycle sharing system data ⋮ Selection of the number of clusters in functional data analysis ⋮ A comparison of the continuous and discrete adjoint approach extended based on the standard lattice Boltzmann method in flow field inverse optimization problems ⋮ Simultaneous variable weighting and determining the number of clusters -- a weighted Gaussian means algorithm ⋮ Data adaptive functional outlier detection: analysis of the Paris bike sharing system data ⋮ A quasi-Bayesian perspective to online clustering

Uses Software

• UCI-ml
• CAPUSHE
• clusfind

Cites Work

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• Finding Groups in Data
• Finding the Number of Clusters in a Dataset
• On the training distortion of vector quantizers
• A Sober Look at Clustering Stability
• Stability of k-Means Clustering
• Asymptotic quantizing error for unbounded random variables (Corresp.)
• The elements of statistical learning. Data mining, inference, and prediction

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