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Classifier Selection Based on Data Complexity Measures

机译:基于数据复杂度测量的分类器选择

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Tin Kam Ho and Ester Bernardò Mansilla in 2004 proposed to use data complexity measures to determine the domain of competition of the classifiers. They applied different classifiers over a set of problems of two classes and determined the best classifier for each one. Then for each classifier they analyzed how the values of some pairs of complexity measures were, and based on this analysis they determine the domain of competition of the classifiers. In this work, we propose a new method for selecting the best classifier for a given problem, based in the complexity measures. Some experiments were made with different classifiers and the results are presented.
机译:2004年锡锦浩和酯伯纳德·曼西拉建议使用数据复杂性措施来确定分类器的竞争领域。它们在两种类别的一组问题上应用了不同的分类器,并确定了每个类的最佳分类器。然后,对于每个分类器,他们分析了一些复杂度措施的值是如何,并且基于该分析,他们确定了分类器的竞争领域。在这项工作中,我们提出了一种基于复杂性度量的给定问题选择最佳分类器的新方法。用不同的分类剂制备一些实验,并提出了结果。

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