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研究了连续属性空间离散化问题 ,将信息熵函数与无穷范数的概念应用到连续属性离散化问题 ,提出了基于信息熵的属性空间极小化算法 .在此基础上 ,提出了连续属性空间上的规则学习算法 .并给出了数值实验结果 .
The discretization problem of continuous attribute space is studied, and the concept of information entropy function and infinitive norm is applied to discretization of continuous attributes, an attribute space minimization algorithm based on information entropy is proposed.On the basis of this, a continuous attribute space On the rules of the learning algorithm and gives the numerical experimental results.