By the method of estimating the probability distribution of training examples, a new and simple method of dealing with numeric attribute based on example distribution and entropy is turned out.
论文分析了基于熵的离散化方法的不足，从估计训练样本的概率分布的角度出发，提出基于样本分布与熵相结合的处理数值型属性的方法。
By the method of estimating the probability distribution of training examples, a new and simple method of dealing with numeric attribute based on example distribution and entropy is turned out.
论文分析了基于熵的离散化方法的不足，从估计训练样本的概率分布的角度出发，提出基于样本分布与熵相结合的处理数值型属性的方法。
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