Matthew G. Smith
Genetic programming with a genetic algorithm for feature construction and selection
Smith, Matthew G.; Bull, Larry
Abstract
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.
Citation
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. https://doi.org/10.1007/s10710-005-2988-7
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Peer Reviewed | Not Peer Reviewed |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 |
DOI | https://doi.org/10.1007/s10710-005-2988-7 |
Keywords | genetic programming, genetic algorithm, feature construction, feature selection, classification, machine learning |
Public URL | https://uwe-repository.worktribe.com/output/1056232 |
Publisher URL | http://dx.doi.org/10.1007/s10710-005-2988-7 |
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