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Chapter

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Title

Coevolutionary feature construction for transformation of representation of machine learners

Authors

[ 1 ] Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | [ P ] employee

Year of publication

2004

Chapter type

chapter in monograph / paper

Publication language

english

Abstract

EN In this paper, a novel method of symbolic feature construction for machine learners is proposed. The method uses evolutionary computation to evolve feature transformation expressions, encoded in a form of fixed-length sequences of predefined elementary operations. Two variants of the method are proposed. One of them involves evolutionary computation for searching the space of possible solutions, whereas the other one engages cooperative coevolution for the same purpose. The results of extensive experimental evaluation on reference machine learning problems indicate superiority of the coevolutionary variety of the proposed approach.

Pages (from - to)

139 - 150

DOI

10.1007/978-3-540-39985-8_15

URL

https://link.springer.com/chapter/10.1007/978-3-540-39985-8_15

Book

Intelligent Information Processing and Web Mining : Proceedings of the International IIS: IIPWM‘04 Conference held in Zakopane, Poland, May 17–20, 2004

Presented on

International IIS: IIPWM‘04 Conference, 17-20.05.2004, Zakopane, Polska

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