The experiments show that, compared with the entropy-based method, our method is simpler in the structure, and can improve the efficiency of classification.
经实验证明，用该方法构造的决策树与传统的基于信息熵方法构造的决策树相比较，复杂性低，且能有效提高分类效果。
Conclusion the efficiency and accuracy of CMI calculation can be improved through optimizing the classification design and calculating method in computer programming.
结论在计算机程序设计中，通过对分组设计及计算方法进行优化，提高了计算cmi的效率及准确性。
In the process of constructing a decision tree, the criteria of selecting partitional attributes will influence the efficiency of classification.
在构造决策树的过程中，分离属性选择的标准直接影响分类的效果。
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