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Evolutionary Feature Selection and Construction

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Encyclopedia of Machine Learning

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Synonyms

EFSC; Evolutionary constructive induction; Evolutionary feature selection; Evolutionary feature synthesis; Genetic attribute construction; Genetic feature selection

Definition

Evolutionary feature selection and construction (EFSC) is a bio-inspired methodology for explicit modification of input data of a learning system. It uses evolutionary computation (EC) to find a mapping from the original data representation space onto a secondary representation space. In evolutionary feature selection (EFS), that mapping consists in dropping off some of the features ( attributes) from the original representation, so the dimensionality of the resulting representation space is not greater than that of the original space. In evolutionary feature construction (EFC), evolutionary algorithm creates (synthesizes) new features (derived attributes) that complement and/or replace the original ones. Therefore, EFS may be considered as special case of EFC.

A typical EFSC algorithm maintains a...

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Authors and Affiliations

    Authors
    1. Krzysztof Krawiec
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    Editors and Affiliations

    1. School of Computer Science and Engineering, University of New South Wales, Sydney, Australia, 2052

      Claude Sammut

    2. Faculty of Information Technology, Clayton School of Information Technology, Monash University, P.O. Box 63, Victoria, Australia, 3800

      Geoffrey I. Webb

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    © 2011 Springer Science+Business Media, LLC

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    Krawiec, K. (2011). Evolutionary Feature Selection and Construction. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_279

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