A Market-based Rule Learning System

9 years 3 months ago
A Market-based Rule Learning System
In this paper, a `market trading' technique is integrated with the techniques of rule discovery and refinement for data mining. A classifier system-inspired model, the market-based rule learning (MBRL) system is proposed and its capability of evolving and refining rules is investigated. Experimental results indicate that the MBRL system is a potentially useful additional tool that can be used to refine neural network extracted rules and possibly discover and add some new, better performance rules. As a result, it can lead to improved performance by increasing the accuracy of the rule inference performance and/or improving the comprehensibility of the rules.
Qingqing Zhou, Martin K. Purvis
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2004
Where ACSW
Authors Qingqing Zhou, Martin K. Purvis
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