This work aims to overcome the use of greedy heuristics and explore the decision tree space in a natural manner. Specifically, genetic algorithms are used to directly evolve binary decision trees in order to find the one that best matches the target concept. Instead of using binary strings, actual decision trees are used as a natural representation of the search space. Additionally, the objective is combined with a simplification motivation in order to evolve accurate yet simple decision trees.
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