文章基本信息

标题：ofw: An R Package to Select Continuous Variables for Multiclass Classification with a Stochastic Wrapper Method
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作者：Kim-Anh Lê Cao ; Patrick Chabrier
期刊名称：Journal of Statistical Software
印刷版ISSN：1548-7660
电子版ISSN：1548-7660
出版年度：2008
卷号：28
期号：1
页码：1-16
语种：English
出版社：University of California, Los Angeles
摘要：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.