An Introduction to Variable and Feature Selection

by: Isabelle Guyon, André Elisseeff

Journal of Machine Learning Research, Vol. 3 (March 2003), pp. 1157-1182.

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Abstract

Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. These areas include text processing of internet documents, gene expression array analysis, and combinatorial chemistry. The objective of variable selection is three-fold: improving the prediction performance of the predictors, providing faster and more cost-effective predictors, and providing a better understanding of the underlying process that generated the data. The contributions of this special issue cover a wide range of aspects of such problems: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.

@article{citeulike:2801724, abstract = {Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. These areas include text processing of internet documents, gene expression array analysis, and combinatorial chemistry. The objective of variable selection is three-fold: improving the prediction performance of the predictors, providing faster and more cost-effective predictors, and providing a better understanding of the underlying process that generated the data. The contributions of this special issue cover a wide range of aspects of such problems: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.}, author = {Guyon, Isabelle and Elisseeff, Andr\'{e} }, citeulike-article-id = {2801724}, journal = {Journal of Machine Learning Research}, keywords = {dimensionality, feature, reduction, selection, variable}, month = {March}, pages = {1157--1182}, posted-at = {2008-05-15 15:25:03}, priority = {2}, title = {An Introduction to Variable and Feature Selection}, url = {http://www.jmlr.org/papers/volume3/guyon03a/guyon03a.pdf}, volume = {3}, year = {2003} }

RIS record

TY - JOUR ID - citeulike:2801724 L3 - citeulike-article-id:2801724 TI - An Introduction to Variable and Feature Selection JF - Journal of Machine Learning Research VL - 3 SP - 1157 EP - 1182 N2 - Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. These areas include text processing of internet documents, gene expression array analysis, and combinatorial chemistry. The objective of variable selection is three-fold: improving the prediction performance of the predictors, providing faster and more cost-effective predictors, and providing a better understanding of the underlying process that generated the data. The contributions of this special issue cover a wide range of aspects of such problems: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods. KW - dimensionality KW - feature KW - reduction KW - selection KW - variable AU - Guyon, Isabelle AU - Elisseeff, André PY - 2003/03// UR - http://www.jmlr.org/papers/volume3/guyon03a/guyon03a.pdf ER -

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