Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/31099
Authors: 
Boulesteix, Anne-Laure
Year of Publication: 
2004
Series/Report no.: 
Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 397
Abstract: 
In the context of binary classification with continuous predictors, we proove two properties concerning the connections between Partial Least Squares (PLS) dimension reduction and between-group PCA, and between linear discriminant analysis and between-group PCA. Such methods are of great interest for the analysis of high-dimensional data with continuous predictors, such as microarray gene expression data.
Subjects: 
Classification
dimension reduction
feature extraction
linear discriminant analysis
partial least squares
principal component analysis
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.