rs-Sparse principal component analysis: A mixed integer nonlinear programming approach with VNS

Principal component analysis is a popular data analysis dimensionality reduction technique, aiming to project with minimum error for a given dataset into a subspace of smaller number of dimensions. In order to improve interpretability, different variants of the method have been proposed in the liter...

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Vydané v:	Computers & operations research Ročník 52; číslo Part B; s. 349 - 354
Hlavní autori:	Carrizosa, Emilio, Guerrero, Vanesa
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Elsevier Ltd 01.12.2014 Pergamon Press Inc
Predmet:	Errors Heuristic Integer programming Mathematical models Mathematical problems Mixed integer Nonlinear mixed integer programming Nonlinear programming Numerical analysis Operations research Principal component analysis Principal components analysis Searching Sparse principal component analysis Sparsity Studies Subspaces Variable neighborhood search Nonlinear mixed integer programming Sparse principal component analysis Variable neighborhood search
ISSN:	0305-0548, 1873-765X, 0305-0548
On-line prístup:	Získať plný text
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