On the quality of \(k\)-means clustering based on grouped data
type: Item
instance of: scholarly article
title: On the quality of \(k\)-means clustering based on grouped data
zbMATH Open document ID: 1169.62059
author: Meelis Käärik
author: K. Pärna
published in: Journal of Statistical Planning and Inference
publication date: 2009-09-14T00:00:00Z
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 65C60
zbMATH DE Number: 5603633
zbMATH Keywords: Lloyd's algorithm
zbMATH Keywords: loss-function
zbMATH Keywords: Voronoi partitions
MaRDI profile type: Publication
full work available at URL: j.jspi.2009.05.021
OpenAlex ID: W2063967481
cites work: Probabilistic models in cluster analysis
cites work: The strong law of large numbers for k-means and best possible nets of Banach valued random variables
cites work: Principal points
cites work: Foundations of quantization for probability distributions
cites work: Quantization
cites work: Q4947403
cites work: Least squares quantization in PCM
cites work: Strong consistency of k-means clustering
DOI: 10.1016/J.JSPI.2009.05.021
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description: scientific article; zbMATH DE number 5603633