Discriminant Partial Least Square on Compositional Data: a Comparison with the Log-Contrast Principal Component Analysis

Gallo, Michele - Mahdi, Smail (2008) Discriminant Partial Least Square on Compositional Data: a Comparison with the Log-Contrast Principal Component Analysis. In: MTISD 2008. Methods, Models and Information Technologies for Decision Support Systems, 18-20 settembre 2008, Lecce.

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URL ufficiale: http://siba-ese.unisalento.it/index.php/MTISD2008/issue/current

Abstract

Discriminant Partial Least Squares for Compositional data (DPLS-CO) was recently proposed by Gallo (2008). The aim of this paper is to show that DPLS-CO is a better dimensionality reduction technique than the LogContrats Principal Component Analysis (LCPCA) for dimensional reduction aimed at discrimination when a compositional training dataset is available.

Tipologia del documento:	Contributo a convegno o workshop (Relazione)
Parole chiave:	Compositional observation, Dimension reduction, Linear discrimination.
Settori scientifico-disciplinari del MIUR:	AREA 13 - Scienze economiche e statistiche > STATISTICA
Codice identificativo (ID):	694
Depositato da:	Prof. Michele Gallo
Depositato il:	19 Ago 2011 09:44
Ultima modifica:	19 Ago 2011 09:44

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