Some methods for dividing continuous attributes in KDD (knowledge discovery in database) and a method based on VDM (value difference metric) are presented.

介绍了在数据库知识发现(KDD)中将连续属性离散化的一些方法，并提出使用值差分度量离散化的算法。

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The algorithm of ID3 usually leans to select attributes which value much more, and can't handle continuous data, and is sensitivity to the noise.

ID 3算法往往偏向于取值较多的属性，不能处理连续数据，对噪声也较为敏感。

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