An Innovative Application of a Constrained-Syntax Genetic Programming System to the Problem of Predicting Survival of Patients

  • Celia C. Bojarczuk
  • Heitor S. Lopes
  • Alex A. Freitas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2610)


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.


Genetic Programming Classification Rule Disjunctive Normal Form Classification Experiment Innovative Application 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Celia C. Bojarczuk
    • 1
  • Heitor S. Lopes
    • 2
  • Alex A. Freitas
    • 3
  1. 1.Departamento de EletrotecnicaCEFET-PRCuritibaBrazil
  2. 2.CPGEI, CEFET-PRCuritibaBrazil
  3. 3.Computing LaboratoryUniversity of KentCanterburyUK

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