Classification of large data sets with mixture models via sufficient EM

DOI10.1016/j.csda.2006.09.014zbMath1445.62153OpenAlexW1969202183MaRDI QIDQ1020219

J. Martínez

Publication date: 29 May 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.09.014

zbMATH Keywords

EM algorithmdata compressionmixture modelsunsupervised classificationweb-usage mining

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

Model-based clustering of high-dimensional data: a review, Estimating random-intercept models on data streams, Narrow big data in a stream: computational limitations and regression, Editorial: Advances in mixture models

Uses Software

• SPSS

Cites Work

• Cure: An efficient clustering algorithm for large databases
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