Smith, RE;
Jiang, MK;
(2007)
MILCS: A mutual information learning classifier system.
In:
(pp. pp. 2945-2952).
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Abstract
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifically designed for supervised learning. MILCS's design draws on an analogy to the structural learning approach of cascade correlation networks. We present preliminary results, and contrast them to results from XCS. We discuss the explanatory power of the resulting rule sets, and introduce a new technique for visualizing explanatory power. Final comments include future directions for this research, including investigations in neural networks and other systems. Copyright 2007 ACM.
| Type: | Proceedings paper |
|---|---|
| Title: | MILCS: A mutual information learning classifier system |
| ISBN: | 159593698X |
| ISBN-13: | 9781595936981 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/1274000.1274063 |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/16132 |
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