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A new method of mining classification rule using relevant concept cover of concept lattice

机译:利用概念格相关概念覆盖的分类规则挖掘新方法

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Classification rule mining is one of important areas of data mining, and it is a hot subject at present. In this paper, we introduce some definitions: relevant concept, pseudo concept, and relevant concept cover. Then we presents an algorithm to compute relevant concept cover, which divides the context into subsets, calculate the set of relevant concepts by the value of concept shannon entropy, and then increasingly constructs relevant concept cover by deleting redundant concept orderly. Finally, we give a new method to classify rules using relevant concept cover of concept lattice, and through experiments prove, the computing speed of this method is faster and the number of rules is more.
机译:分类规则挖掘是数据挖掘的重要领域之一,是当前的热门话题。在本文中,我们介绍一些定义:相关概念,伪概念和相关概念覆盖。然后我们提出了一种计算相关概念覆盖的算法,该算法将上下文划分为子集,通过概念香农熵的值计算相关概念的集合,然后通过有序删除多余的概念来逐步构建相关概念覆盖。最后,给出了一种利用概念格的相关概念覆盖对规则进行分类的新方法,并通过实验证明,该方法的计算速度更快,规则数量更多。

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