Discriminant Partial Least Square on Compositional Data: a Comparison with the Log-Contrast Principal Component Analysis
Gallo, Michele and 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.
Official URL: http://siba-ese.unisalento.it/index.php/MTISD2008/issue/current
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.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||Compositional observation, Dimension reduction, Linear discrimination.|
|Subjects:||AREA 13 - Scienze economiche e statistiche > STATISTICA|
|Deposited By:||Prof. Michele Gallo|
|Deposited On:||19 Aug 2011 09:44|
|Last Modified:||19 Aug 2011 09:44|
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