本文提出了一个新的决策表离散化算法，该算法在离散化数据的同时具有良好的属性约简功能。

In this paper, a novel decision table discretization algorithm is presented, which has fine attribute reduction function in time of data discretization and increases quality of classification.

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随后论文重点对作者在数据离散和属性约简两个方面做的研究工作进行了阐述。

Then the author's researches on data discretization and attribute reduction are introduced in detail.

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属性约简是数据挖掘预处理中非常重要的一步，它通过减少信息的维数提高数据挖掘算法的效率。

Attribute reduction is one of important step in preprocessing of data mining, it improves the efficiency of the data mining algorithm by reducing the dimensions of the information.

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