ZHANG Wen-yang,JIANG Yu.Attribute Reduction with Rough Set based on Digital Search Trees[J].Journal of Chengdu University of Information Technology,2017,(06):618-622.[doi:10.16836/j.cnki.jcuit.2017.06.009]
基于键树的粗糙集属性约简算法
- Title:
- Attribute Reduction with Rough Set based on Digital Search Trees
- 文章编号:
- 2096-1618(2017)06-0618-05
- 分类号:
- TP18
- 文献标志码:
- A
- 摘要:
- 属性约简是粗糙集理论研究的核心内容之一。差别矩阵因其简洁、直观而被广泛应用于属性约简中,但其包含了大量冗余元素,从而造成存储空间的极大浪费。基于键树的思想,提出一种对差别矩阵非空元素存储的新方法,该方法消除了差别矩阵中的重复元素,并使部分具有子父关系的元素共享键树中父集所在的路径,从而实现了对差别矩阵的压缩存储。最后,基于该键树提出了一属性约简算法。
- Abstract:
- Attribute reduction plays a key role in rough set. Discernibility matrix is efficient in finding out reducts.However, there are many redundancy non-empty elements in discernibility matrix.In order to eliminate the related redundancy and pointless elements, in this paper, a new method to store elements in discernibility matrix was proposed based on digital search trees. And an algorithm is presented to address Pawlak reduction based on this new structure.The experimentresults show that the proposed algorithm is efficient in finding out an attribute reduction.
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相似文献/References:
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SONG Jian,JIANG Yu,LI Dong,et al.Attribute Reduction with Rough Set based on Binary Linked List[J].Journal of Chengdu University of Information Technology,2019,(06):112.[doi:10.16836/j.cnki.jcuit.2019.02.002]
备注/Memo
收稿日期:2017-06-06 基金项目:四川省教育厅重点资助项目(17ZA0071); 国家自然科学基金青年基金资助项目(61602064); 四川省科技计划-重点研发资助项目(2017HH0088)