PCA and PLS with very large data sets

DOI10.1016/j.csda.2003.11.027zbMath1429.62220OpenAlexW2022466155MaRDI QIDQ957080

Anders Berglund, Svante Wold, Nouna Kettaneh

Publication date: 26 November 2008

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

Full work available at URL: https://doi.org/10.1016/j.csda.2003.11.027

zbMATH Keywords

clusteringdata miningprincipal componentsPLSdata preprocessing

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics (62P99)

Related Items (4)

Multicriteria variable selection for classification of production batches ⋮ Principles of experimental design for big data analysis ⋮ MKPLS approach: switching strategies for the non-linear multi-kernel PLSR ⋮ Editorial: Machine learning and robust data mining

Cites Work

• On partial least squares dimension reduction for microarray-based classification: a simulation study
• Pattern recognition by means of disjoint principal components models
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