但是属性约简是一个NP问题，对属性的约简和决策规则的约简只能通过启发式算法实现。

But the attribute reduction is a NP problem, the attribution reduction and decision rule reduction will be solved by method of elicitation.

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提出了一种基于条件信息熵的知识约简启发式算法，并指出该算法的时间复杂度是多项式的。

A heuristic algorithm based on conditional information entropy for knowledge reduction is proposed, and the complexity of this algorithm is analyzed.

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提出了一种基于条件粒度熵的属性约简的启发式算法，通过例子分析，表明该算法是有效的。

The paper offer a new heuristic attribute reduction algorithm based on conditional granularity entropy, though running an example, we show that this algorithm is effective.

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