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Entropy-Based Estimation in Classification Problems

机译:基于熵的分类问题估计

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摘要

The problem of binary classification is considered, an algorithm for its solution is proposed, based on the method of entropy-based estimation of the decision rule parameters. A detailed description of the entropy-based estimation method and the classification algorithm is given, the advantages and disadvantages of this approach are described, the results of numerical experiments and comparisons with the traditional support vector machine for classification accuracy and degree of dependence on the training sample size are presented.
机译:考虑了二进制分类问题,基于判决规则参数的基于熵的估计方法,提出了一种解决方案的算法。 给出了基于熵的估计方法和分类算法的详细描述,描述了这种方法的优点和缺点,数值实验和与传统支持向量机的比较结果,用于分类准确性和对训练程度的依赖程度 提出了样品大小。

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