An innovative application of a constrained-syntax genetic programming system to the problem of predicting survival of patients

Authors:
Celia C. Bojarczuk;Heitor S. Lopes;Alex A. Freitas
Affiliations:
Departamento de Eletrotecnica, CEFET-PR, Curitiba, Brazil;CPGEI, CEFET-PR, Curitiba, Brazil;Computing Laboratory, University of Kent, Canterbury, UK
Venue:
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Year:
2003

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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.