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.
Journal Article Type | Article |
---|---|
Publication Date | Sep 1, 2005 |
Journal | Genetic Programming and Evolvable Machines |
Print ISSN | 1389-2576 |
Electronic ISSN | 1573-7632 |
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Peer Reviewed | Not Peer Reviewed |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 |
You might also like
Towards the evolution of vertical-axis wind turbines using supershapes
(2014)
Journal Article
Evolving unipolar memristor spiking neural networks
(2015)
Journal Article
Evolving functional and structural dynamism in coupled boolean networks
(2014)
Journal Article
A brief history of learning classifier systems: from CS-1 to XCS and its variants
(2015)
Journal Article
Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system
(2013)
Journal Article
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search