基于最大熵原理的决策表最小属性数

Min Dong, HuiYu Jiang
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引用次数: 1

摘要

决策表一直是数据挖掘中非常重要的对象。人们往往需要更简单的决策表,以减少表的规模。但决策表并不总是最简单的,所以我们必须尝试简化它,以了解哪些条件属性是必要的。已知约简结果通常不是唯一的,同一表的不同扣除表中设置的条件属性基数不同。然而,从约简表的研究成果中,我们可以找到一个最简单的条件属性集,称之为最小属性集。本文根据信息论,推导出最小属性集基数的计算公式,称为最小属性数。而且,在化简之前,我们只能知道这个表是不是最简单的表。最后,我们给出一个简单的测试示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Minimum Attribute Number in Decision Table Based on Maximum Entropy Principle
Decision tables are always extremely important objects in data mining. People often require the more simple decision table in order to reduce the scale of tables. But a decision table is not always the most simple, so we have to try reducting it to learn which condition attributes are essential. It is known that the reduct results are not usually unique and the cardinal numbers of condition attributes set in different deducted tables of the same tables are different. From research findings on reducted tables, however, we can find out a simplest condition attributes set and call it Minimum Attribute Set. According to information theory, in this paper, we have deduced a formula to calculate the cardinal number of the Minimum Attribute Set, which is called Minimum Attribute Number. Moreover, before reducted we can just know whether the table is the simplest one or not. Eventually, we give a simple test example.
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