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Integrating Multiple Classifiers in a GA-based Inductive Learning Environment  

Kim, Yeong-Joon (상명대학교 소프트웨어학부)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.10, no.3, 2006 , pp. 614-621 More about this Journal
Abstract
We have implemented a multiclassifier learning approach in a GA-based inductive learning environment that learns classification rules that are similar to rules used in PROSPECTOR. In the multiclassifier learning approach, a classification system is constructed with several classifiers that are obtained by running a GA-based learning system several times to improve the overall performance of a classification system. To implement the multiclassifier learning approach, we need a decision-making scheme that can draw a decision using multiple classifiers. In this paper, we introduce two decision-making schemes: one is based on combining posterior odds given by classifiers to each class and the other one is a voting scheme based on ranking assigned to each class by classifiers. We also present empirical results that evaluate the effect of the multiclassifier learning approach on the GA-based inductive teaming environment.
Keywords
PROSPECTOR;
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