Abstract
In this paper we present a classifier system based on Genetic Algorithms for a medical domain. The system evolves a set of rules, using the Pittsburgh approach. Therefore, each individual of the Genetic Algorithm codifies a complete set of rules. Our efforts have focused on the improvement of classification and prediction accuracy and the minimization of the number of rules required to describe the problem. In order to study the behaviour of our system in these areas, several experiments are presented.
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Mansilla, E.B.i., Mekaouche, A., Guiu, J.M.G.i. (1999). A Study of a Genetic Classifier System Based on the Pittsburgh Approach on a Medical Domain. In: Imam, I., Kodratoff, Y., El-Dessouki, A., Ali, M. (eds) Multiple Approaches to Intelligent Systems. IEA/AIE 1999. Lecture Notes in Computer Science(), vol 1611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48765-4_21
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DOI: https://doi.org/10.1007/978-3-540-48765-4_21
Publisher Name: Springer, Berlin, Heidelberg
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