Abstract
This paper proposes a constrained-syntax genetic programming (GP) algorithm for discovering classification rules in medical data sets. The proposed GP contains several syntactic constraints to be enforced by the system using a disjunctive normal form representation, so that individuals represent valid rule sets that are easy to interpret. The GP is compared with C4.5 in a real-world medical data set. This data set represents a difficult classification problem, and a new preprocessing method was devised for mining the data.
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© 2003 Springer-Verlag Berlin Heidelberg
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Bojarczuk, C.C., Lopes, H.S., Freitas, A.A. (2003). An Innovative Application of a Constrained-Syntax Genetic Programming System to the Problem of Predicting Survival of Patients. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E., Poli, R., Costa, E. (eds) Genetic Programming. EuroGP 2003. Lecture Notes in Computer Science, vol 2610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36599-0_2
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DOI: https://doi.org/10.1007/3-540-36599-0_2
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