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Exploring the power of genetic search in learning symbolic classifiers | IEEE Journals & Magazine | IEEE Xplore

Exploring the power of genetic search in learning symbolic classifiers


Abstract:

In this paper we show, in a constructive way, that there are problems for which the use of genetic algorithm based learning systems can be at least as effective as tradit...Show More

Abstract:

In this paper we show, in a constructive way, that there are problems for which the use of genetic algorithm based learning systems can be at least as effective as traditional symbolic or connectionist approaches. To this aim, the system REGAL is briefly described, and its application to two classical benchmarks for machine learning is discussed, by comparing the results with the best ones published in the literature.
Page(s): 1135 - 1141
Date of Publication: 06 August 2002

ISSN Information: