GA Tree: genetically evolved decision trees

  title={GA Tree: genetically evolved decision trees},
  author={Athanassios Papagelis and Dimitrios Kalles},
We explore the use of genetic algorithms to directly evolve classification decision trees. Instead of using binary strings, we adopt a natural representation of the problem using binary tree structures. We argue on the suitability of such a concept learner due to its ability to efficiently search complex hypotheses spaces and discover conditionally dependent as well as irrelevant attributes. The performance of the system is measured on a set of artificial and standard discretized concept… CONTINUE READING
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