Classification of Epidemiological Data: A Comparison of Genetic Algorithm and Decision Tree Approaches

Abstract

This paper describes an application of genetic algorithms (GA’s) to classify epidemiological data, which is often challenging to classify due to noise and other factors. For such complex data (that requires a large number of very specific rules to achieve a high accuracy), smaller rule sets, composed of more general rules, may be preferable, even if they… (More)

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Cite this paper

@inproceedings{Congdon2000ClassificationOE, title={Classification of Epidemiological Data: A Comparison of Genetic Algorithm and Decision Tree Approaches}, author={Clare Bates Congdon}, year={2000} }