【作者】 崔洪晶；

【导师】 杨静；

【作者基本信息】 哈尔滨工程大学 ， 计算机软件与理论， 2007， 硕士

【摘要】 粗糙集理论是20世纪70年代发展起来的一种新的处理含糊性和不确定性问题的数学工具，它是智能信息处理的一种重要方法，基于不可区分性思想和知识简化方法。目前，获得高效、快捷的属性约简算法是该理论研究的主要课题之一，高效的约简算法在信息系统分析与数据挖掘等领域具有重要的应用意义。本文在研究粗糙集理论的基础上发现由于信息系统中的决策规则存在相容的和不相容的，导致决策表的相容性和不可相容性。而大多数决策表属性约简算法在进行属性约简之前需要判断决策表的相容性。针对决策表的可相容性和不可相容性，分别研究了相应代表的属性约简算法。相容决策表约简算法包括基于依赖度和重要度的属性约简算法和基于广义信息表的属性约简算法；在不相容约简算法中，介绍了基于包含度的属性约简算法。通过分析表明以上算法只能对相容和不相容决策表分别约简，浪费了时间，不具一般性。为了解决这一问题，本文提出了基于决策熵的决策表属性约简算法，通过实验分析，其实验结果与前三个算法结果一致。表明基于决策熵的属性约简算法对决策表进行属性约简之前，不需要预先判断决策表是相容的或不相容的，并且解决了经典粗糙集理论中属性约简的两种定义对不相容决策表约简时结果不一致的问题，提高了效率，具有广泛性，达到了预期效果。更多还原

【Abstract】 Rough Set theory is a new mathematical tool which can tackle ambiquity and uncertainty developed from the 1970s. It is an important method of intellective information transaction, which based of non-distinguish and technoledge reduction. At present, it’s one of the important problems of calculating high effictive, shortcut attribute reduction algorithms, and the high effictive reduction algorithms have important application significance in information system analysis and data mining.This paper is based on rough set theory, due to there is consistence and inconsistence in decision rule of information system, which results in consistence and inconsistence of decision table. However most of attribute reduction algorithms of decision table need to judge whether decision table is consistent or inconsistent before progressing attribute reduction. Aiming at consistent or inconsistent of decision table, researches representative attribute reduction algorithms respectively. Consistent decision table includes an algorithm of attribute reduction based on dependence and importance and an algorithm of attribute reduction based on generalized information table; while an algorithm of attribute reduction based on inclusion degree in the inconsistent of decision table. It learned that above attribute reduction algorithms may only reduce consistent or inconsistent decision table respectively, wasting of most time, and they had not universality. In order to takle that, a proposed algorithm of attribute reduction for decision table based on entropy is pointed. The experiment result and above ones are accordant through analyzing. The new algorithm need not judge whether decision table is consistent or inconsistent before progressing attribute reduction for decision tables. When these definitions are used to reduce inconsistent decision table, reduction results could be inconsistent, it solves this problem and advances efficiency. It has universality and reaches anticipative effect.更多还原