Data reduction: feature selection

Authors:
Hiroshi Motoda;Huan Liu
Affiliations:
Professor of Intelligent Systems Science, The Institute of Scientific and Industrial Research, Osaka University, Japan;Associate Professor of Computer Science and Engineering, Arizona State University, Tempe
Venue:
Handbook of data mining and knowledge discovery
Year:
2002

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Abstract

Feature selection is introduced as a search problem that consists of feature subset generation, evaluation, and selection. The purpose of feature selection is three-fold: reducing the number of features, improving classification accuracy, and simplifying the learned representation. We review major evaluation measures and various feature selection approaches, list some existing methods, and show by example the role of feature selection in data mining.