ofw: an R package to select continuous variables for multiclass classification with a stochastic wrapper method

Kim-Anh Lê Cao (1, 2) , Patrick Chabrier (3)

1 IMT - Institut de Mathématiques de Toulouse UMR5219
2 SAGA - Station d'Amélioration Génétique des Animaux
3 UBIA - Unité de Biométrie et Intelligence Artificielle (ancêtre de MIAT)

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" (OFW). 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 of OFW are proposed with the application of supervised multiclass classifiers such as CART and SVM. Furthermore, a weighted approach can be chosen to deal with unbalanced multiclasses, a common characteristic in microarray data sets. ofw is freely available as an R package under the GPL license. The package can be downloaded from the Comprehensive R Archive Network (CRAN).

Mots clés: microarray

Domaines: Génomique, Transcriptomique et Protéomique [q-bio.GN]

Kim-Anh Lê Cao, Patrick Chabrier. ofw: an R package to select continuous variables for multiclass classification with a stochastic wrapper method. 2008. ⟨hal-00300209⟩