Attribute reduction and value reduction are the basis of learning from examples based on rough sets.
属性约简和属性值约简是基于粗集理论进行有导师学习的基础。
参考来源 - 基于粗集理论的机器学习·2,447,543篇论文数据，部分数据来源于NoteExpress
将属性值约简和数据挖掘相结合，给出支持度、置信度、覆盖度的定义。
This paper associates attributive value reduction with data mining and proposed three concepts: support, confidence and coverage.
然后在属性值约简中进一步去除与用户无关的属性，从而抽取个性化决策规则。
Secondly, during reduction of attribute values, some irrelevant attributes are further eliminated, then abstractation of personalized decision rules is accomplished.
通过算法复杂度分析说明，该算法在一定程度上解决了属性值约简的NP难问题。
The algorithm complexity analysis shows that, to a certain extent, the algorithm could resolve the NP hard problems of attributive value reduction.
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