 ofw: An R Package to Select Continuous Variables for Multiclass Classification with a Stochastic Wrapper MethodKim-Anh Lê Cao and Patrick Chabrier Journal of Statistical Software, 2008, vol. 028, issue i09 Abstract: When dealing with high dimensional and low sample size data, feature selection is often needed to help reduce the dimension of the variable space while optimizing the classification task. Few tools exist for selecting variables in such data sets, especially when classes are numerous (>2). We have developed ofw, an R package that implements, in the context of classification, the meta algorithm "optimal feature weighting". We focus on microarray data, although the method can be applied to any p >> n problems with continuous variables. The aim is to select relevant variables and to numerically evaluate the resulting variable selection. Two versions are proposed with the application of supervised multiclass classifiers such as classification and regression trees and support vector machines. Furthermore, a weighted approach can be chosen to deal with unbalanced multiclasses, a common characteristic in microarray data sets. Date: 2008-11-17 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:028:i09 Access Statistics for this article Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis More articles in Journal of Statistical Software from Foundation for Open Access Statistics |
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