Rough set data analysis in the knowledge discovery in database (KDD) is different to other KDD methods, especially with respect to model assumption.
粗集数据分析不同于其它知识发现方法，特别在模型假设方面的一种方法。
Rough set data analysis doesn't need any other information but data set, simultaneously, the results obtained are usually short of statistical evidence.
粗糙集方法虽然不需要数据之外的其它信息，但所得结果同时也缺乏统计证据。
Four kinds of condition entropy are defined in this paper. Accordingly, four kinds of entropy based methods for the attribute reduction in the rough set data analysis are proposed.
本文定义了四种条件熵，并在此基础上提出了四种基于熵的方法，以用于粗糙集数据分析中的属性简约。
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