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Genetic programming with a genetic algorithm for feature construction and selection

Smith, Matthew G.; Bull, Larry


Matthew G. Smith

Lawrence Bull
School Director (Research & Enterprise) and Professor


The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we primarily examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is classified using the C4.5 decision tree learning algorithm. Genetic Programming is used to construct new features from those available in the data, a potentially significant process for data mining since it gives consideration to hidden relationships between features. A Genetic Algorithm is used to determine which such features are the most predictive. Using ten well-known datasets we show that our approach, in comparison to C4.5 alone, provides marked improvement in a number of cases. We then examine its use with other well-known machine learning techniques. © 2005 Springer Science + Business Media, Inc.


Smith, M. G., & Bull, L. (2005). Genetic programming with a genetic algorithm for feature construction and selection. Genetic Programming and Evolvable Machines, 6(3), 265-281.

Journal Article Type Article
Publication Date Sep 1, 2005
Journal Genetic Programming and Evolvable Machines
Print ISSN 1389-2576
Publisher Springer (part of Springer Nature)
Peer Reviewed Not Peer Reviewed
Volume 6
Issue 3
Pages 265-281
Keywords genetic programming, genetic algorithm, feature construction, feature selection, classification, machine learning
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