Selection of Variables for Cluster Analysis and Classification Rules

DOI10.1198/016214508000000544zbMath1205.62077arXivmath/0610757OpenAlexW2079896089MaRDI QIDQ3069865

Ana Justel, Marcela Svarc, Ricardo Fraiman

Publication date: 1 February 2011

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0610757

zbMATH Keywords

pattern recognitionforward-backward algorithmfinding relevant variables

Mathematics Subject Classification ID

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

Related Items (9)

Feature selection for functional data ⋮ Searching for the core variables in principal components analysis ⋮ A divisive clustering method for functional data with special consideration of outliers ⋮ Variable selection in model-based clustering and discriminant analysis with a regularization approach ⋮ Seeking relevant information from a statistical model ⋮ Modelling the role of variables in model-based cluster analysis ⋮ Pattern recognition via projection-based \(k\)NN rules ⋮ Dissimilarity and similarity measures for comparing dendrograms and their applications ⋮ Data science, big data and statistics

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