Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/30993
Authors: 
Boulesteix, Anne-Laure
Year of Publication: 
2004
Series/Report no.: 
Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 392
Abstract: 
PLS dimension reduction is known to give good prediction accuracy in the context of classification with high-dimensional microarray data. In this paper, PLS is compared with some of the best state-of-the-art classification methods. In addition, a simple procedure to choose the number of components is suggested. The connection between PLS dimension reduction and gene selection is examined and a property of the first PLS component for binary classification is proven. PLS can also be used as a visualization tool for high-dimensional data in the classification framework. The whole study is based on 9 real microarray cancer data sets.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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