Parameter Optimization in Decision Tree Learning by using Simple Genetic Algorithms

نویسنده

  • MICHEL CAMILLERI
چکیده

The process of identifying the optimal parameters for an optimization algorithm or a machine learning one is a costly combinatorial problem because it involves the search of a large, possibly infinite, space of candidate parameter sets. Our work compares grid search with a simple genetic algorithm when used to find the optimal parameter setting for an ID3 like learner operating on given datasets. Key–Words: Machine Learning, Evolutionary Algorithms, Parameter Optimization

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تاریخ انتشار 2014