本课题的研究有利于提高机械产品系统分类与决策的客观性与准确性，提高分类的自动化水平。

The research improves the objectivity and accuracy of the classification and decision-making of mechanical products system; it also enhances the automatization level of classification.

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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。

The experiments show that, compared with the entropy-based method, our method is simpler in the structure, and can improve the efficiency of classification.

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避开图像相似度大小的定义，通过决策表理论解决图像的分类与检索问题。

To avoid the similarity definition of images, classification and searching problems of images are solved through decision-making table theory.

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