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An Introduction to Variable and Feature Selection

Journal of machine learning Research 3 (2003) 1157-1182 Submitted 11/02; Published 3/03An Introduction to Variable and Feature SelectionIsabelle Creston RoadBerkeley, CA 94708-1501, USAAndr e Inference for machine learning and Perception DepartmentMax Planck Institute for Biological CyberneticsSpemannstrasse 3872076 T ubingen, GermanyEditor:Leslie Pack KaelblingAbstractVariable and Feature Selection have become the focus of muchresearch in areas of application forwhich datasets with tens or hundreds of thousands of variables are available. These areas includetext processing of internet documents, gene expression array analysis, and combinatorial objective of Variable Selection is three-fold: improving the prediction performance of the pre-dictors, providing faster and more cost-effective predictors, and providing a better understanding ofthe underlying process that generated the data.

outside of the scope of machine learning, so we focus here on building predictors. We consider in this section ranking criteria defined for individual variables, independe ntly of the context of others. Correlation methods belong to that category. We also limit ourselves to supervised learning criteria.

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