计算机科学 ›› 2018, Vol. 45 ›› Issue (10): 229-234.doi: 10.11896/j.issn.1002-137X.2018.10.042

• 人工智能 • 上一篇    下一篇

优势关系下基于浓缩布尔矩阵的属性约简方法

李艳, 郭娜娜, 吴婷婷, 湛燕   

  1. 河北大学数学与信息科学学院河北省机器学习与计算智能重点实验室 河北 保定071002
  • 收稿日期:2017-08-16 出版日期:2018-11-05 发布日期:2018-11-05
  • 作者简介:李 艳(1976-),女,博士,教授,CCF会员,主要研究方向为机器学习、Rough集理论、计算智能,E-mail:ly@hbu.cn(通信作者);郭娜娜(1992-),女,硕士生,主要研究方向为粒计算与知识发现,E-mail:1498976702@qq.com;吴婷婷(1989-),女,硕士生,主要研究方向为粒计算与知识发现;湛 燕(1978-),女,副教授,主要研究方向为机器学习。
  • 基金资助:
    国家自然科学基金(61170040,61473111),河北大学自然科学研究计划项目(799207217069)资助

Attribute Reduction Based on Concentration Boolean Matrix under Dominance Relations

LI Yan, GUO Na-na, WU Ting-ting, ZHAN Yan   

  1. Key Lab of Machine Learning and Computational Intelligence,College of Mathematics and Information Science, Hebei University,Baoding,Hebei 071002,China
  • Received:2017-08-16 Online:2018-11-05 Published:2018-11-05

摘要: 在优势关系粗糙集方法(DRSA)的框架下,针对不协调的目标信息系统求属性约简。基于优势矩阵的方法是最常用的一类约简方法,但矩阵中不是所有的元素都有效。浓缩优势矩阵只保留对求约简有用的最小属性集,因而可以明显降低约简过程中的计算量。进一步地,浓缩布尔矩阵通过布尔代数的形式有效地弥补了优势矩阵生成效率低的缺点。文中将等价关系上的浓缩布尔矩阵属性约简方法扩展到优势关系上,针对优势矩阵提出了浓缩布尔矩阵的概念,建立了相应的高效约简方法,使效率得到明显提高。最后采用9组UCI数据进行实验,结果验证了所提方法的有效性。

关键词: 粗糙集, 浓缩布尔矩阵, 浓缩优势矩阵, 优势关系, 属性约简

Abstract: Under the framework of dominance relation-based rough set approach (DRSA),attribute reduction was stu-died for inconsistent target information systems.The methods based on dominance matrix are the most commonly used ones,but not all elements in the matrix are valid.The concentration dominance matrix only preserves the smallest set of attributes which are useful for attribute reduction,and thus the computational complexity can be significantly reduced.On the other side,the concentration Boolean matrix further improves the generation efficiency of the dominance matrix by Boolean algebra.This paper extended the concentration Boolean matrix method under equivalence relations to that under dominance relations.The concept of concentration Boolean matrix was proposed for the dominance matrix,and the corresponding efficient reduction method was established to improve the efficiency of the reduction algorithm.Finally,nine UCI data sets were used in the experiments,and the results show the feasibility and effectiveness of the proposed method.

Key words: Attribute reduction, Concentration boolean matrix, Concentration dominance matrix, Dominance relation, Rough set

中图分类号: 

  • TP181
[1]PAWLAK Z.Rough set[J].International Journal of Computer and Information Science,1982,11(5):341-356.
[2]QIAN Y H,LIANG J Y,PEDRYCZ W.An efficient accelerator for attribute reduction from incomplete data in rough set framework[J].Pattern Recognition,2011,44(8):1658-1670.
[3]BLASZCZYNSKI J,GRECO S,SLOWINSKI R.Inductive discovery of laws using monotonic rules[J].Engineering Applications of Artificial Intelligence,2012,25(2):284-294.
[4] ABBAS A,LIU J.Designing an intelligent recommender system using partial credit model and Bayesian rough set[J].International Arab Journal of Information Technology,2012,9(2):179-187.
[5]CHANG B,HUNG H.A study of using RST to create the supplier selection model and decision making rules[J].Expert Systems with Applications,2010,37(12):8284-8295.
[6]LIU D,YAO Y Y,LI T R.Three-way investment decisions with decision-theoretic rough sets[J].International Journal of Computational Intelligence Systems,2011,4(1):66-74.
[7]WEI L,LI H R,ZHANG W X.Knowledge reduction based on the equivalence relations defined on attribute set and its power set[J].Information Sciences,2007,177(15):3178-3185.
[8]CHEN X,ZIARKO W.Experiments with rough set approach to face recognition[J].International Journal of Intelligent Systems,2011,26(6):499-517.
[9]KARAMI J,ALIMOHAMMADI A,SEIFOURI T.Water quality analysis using a variable consistency dominance-based rough set approach[J].Computers,Environment and Urban Systems,2014,43:25-33.
[10]CHANG B,HUNG H.A study of using RST to create the supplier selection model and decision making rules[J].Expert Systems with Applications,2010,37(12):8284-8295.
[11]LIU D,YAO Y Y,LI T R.Three-way investment decisions with decision-theoretic rough sets[J].International Journal of Computational Intelligence Systems,2011,4(1):66-74.
[12]刘清.Rough集及Rough推理[M].北京:科学出版社,2001.
[13]GRECO S,MATARAZZO B,SLOWINSKI R.Rough sets theory for multicriteria decision analysis[J].European Journal of Operational Research,2001,129(1):1-47.
[14]GRECO S,MATARAZZO B,SLOWINSKI R.Rough approxi- mation by dominance relations[J].International Journal of Intelligent Systems,2002,17(2):153-171.
[15]GRECO S,SLOWINSKI R,MATARAZZO B,et al.Variable consistency model of dominance-based rough sets approach[C]∥Proc.of International Conference on Rough Sets and Current Trends in Computing,LNAI,2005.Springer,Berlin,2005:170-181.
[16]张文修,梁怡,吴伟志.信息系统与知识发现[M].北京:科学出版社,2005.
[17]LI S Y,LI T R,LIU D.Dynamic maintenance of approximations in dominance-based rough set approach under the variation of the object set[J].International Journal of Intelligent Systems,2013,28(8):729-751.
[18]CHEN H M,LI T R.Parallel attribute reduction in dominance-based neighborhood rough set[J].Information Sciences,2016,373(12):351-368.
[19]XU W H,ZHANG W X.Consistent approximation spaces based on dominance relations[J].Computer Science,2005,32(9):164-165.(in Chinese)
徐伟华,张文修.基于优势关系下协调近似空间[J].计算机科学,2005,32(9):164-165.
[20]ZHENG J Y,WANG H.Distribution Reduction of Inconsistent Interval-valued Target Information System Based on Dominance Relation[J].The Practice and Understanding of Mathematics,2016,46(6):129-135.(in Chinese)
郑俊艳,王虹.基于优势关系的不协调区间值目标信息系统的分布约简[J].数学的实践与认识,2016,46(6):129-135.
[21]BAO A N,JIANG H B.An Improved Distributed Reduction and Maximum Distribution Reduction Method[J].Henan Science and Technology,2014(13):189-190.(in Chinese)
鲍爱娜,姜洪冰.一种改进的分布约简与最大分布约简求法[J].河南科技,2014(13):189-190.
[22]FANG L H,LI K D.Distribution Reduction Based on Unequal Target Information System under Dominant-Equivalent Relation[J].Fuzzy Systems and Mathematics,2013,27(3):182-189.(in Chinese)
方连花,李克典.基于优势-等价关系下不协调目标信息系统的分布约简[J].模糊系统与数学,2013,27(3):182-189.
[23]XIE W Q,LIN G P.Distribution Reduction of Interval-valued Target Information System under Dominant-Equivalent Relation[J].Journal of Qiqihar University,2016,32(6):72-77.(in Chinese)
谢文琼,林国平.优势-等价关系下区间值目标信息系统的分布约简[J].齐齐哈尔大学学报,2016,32(6):72-77.
[24]CHEN D G,ZHAO S Y,ZHANG L,et al.Sample pair selection for attribute reduction with rough set[J].IEEE Transactions on Knowledge and Data Engineering,2012,24(11):2080-2093.
[25]YANG M,YANG P.Discemibility matrix enriching and computation for attributes reduction[J].Computer Science,2006,33(9):181-183.(in Chinese)
杨明,杨萍.差别矩阵浓缩及其属性约简求解方法[J].计算机科学,2006,33(9):181-183.
[26]HUANG Q,WEI L.Attribute Reduction Method of Sequential Information System Based on Boolean Matrix[J].Small Microcomputer System,2016,37(8):1717-1720.(in Chinese)
黄琴,魏玲.基于布尔矩阵的序信息系统属性约简方法[J].小型微型计算机系统,2016,37(8):1717-1720.
[27]YIN Z W,ZHANG J P.An attribute reduction algorithm Based on a concentration Boolean matrix[J].Journal of Harbin Engineering University,2009,30(3):307-311.(in Chinese)
殷志伟,张健沛.基于浓缩布尔矩阵的属性约简算法[J].哈尔滨工程大学学报,2009,30(3):307-311.
[28]ZHU J H,XU Z Y.An efficient attribute reduction algorithm for improved boolean conflict matrix[J].Computer Engineering and Applications,2017,53(6):145-149.(in Chinese)
朱金虎,徐章艳.改进的布尔冲突矩阵的高效属性约简算法[J].计算机工程与应用,2017,53(6):145-149.
[1] 程富豪, 徐泰华, 陈建军, 宋晶晶, 杨习贝.
基于顶点粒k步搜索和粗糙集的强连通分量挖掘算法
Strongly Connected Components Mining Algorithm Based on k-step Search of Vertex Granule and Rough Set Theory
计算机科学, 2022, 49(8): 97-107. https://doi.org/10.11896/jsjkx.210700202
[2] 许思雨, 秦克云.
基于剩余格的模糊粗糙集的拓扑性质
Topological Properties of Fuzzy Rough Sets Based on Residuated Lattices
计算机科学, 2022, 49(6A): 140-143. https://doi.org/10.11896/jsjkx.210200123
[3] 方连花, 林玉梅, 吴伟志.
随机多尺度序决策系统的最优尺度选择
Optimal Scale Selection in Random Multi-scale Ordered Decision Systems
计算机科学, 2022, 49(6): 172-179. https://doi.org/10.11896/jsjkx.220200067
[4] 陈于思, 艾志华, 张清华.
基于三角不等式判定和局部策略的高效邻域覆盖模型
Efficient Neighborhood Covering Model Based on Triangle Inequality Checkand Local Strategy
计算机科学, 2022, 49(5): 152-158. https://doi.org/10.11896/jsjkx.210300302
[5] 孙林, 黄苗苗, 徐久成.
基于邻域粗糙集和Relief的弱标记特征选择方法
Weak Label Feature Selection Method Based on Neighborhood Rough Sets and Relief
计算机科学, 2022, 49(4): 152-160. https://doi.org/10.11896/jsjkx.210300094
[6] 王子茵, 李磊军, 米据生, 李美争, 解滨.
基于误分代价的变精度模糊粗糙集属性约简
Attribute Reduction of Variable Precision Fuzzy Rough Set Based on Misclassification Cost
计算机科学, 2022, 49(4): 161-167. https://doi.org/10.11896/jsjkx.210500211
[7] 王志成, 高灿, 邢金明.
一种基于正域的三支近似约简
Three-way Approximate Reduction Based on Positive Region
计算机科学, 2022, 49(4): 168-173. https://doi.org/10.11896/jsjkx.210500067
[8] 薛占熬, 侯昊东, 孙冰心, 姚守倩.
带标记的不完备双论域模糊概率粗糙集中近似集动态更新方法
Label-based Approach for Dynamic Updating Approximations in Incomplete Fuzzy Probabilistic Rough Sets over Two Universes
计算机科学, 2022, 49(3): 255-262. https://doi.org/10.11896/jsjkx.201200042
[9] 李艳, 范斌, 郭劼, 林梓源, 赵曌.
基于k-原型聚类和粗糙集的属性约简方法
Attribute Reduction Method Based on k-prototypes Clustering and Rough Sets
计算机科学, 2021, 48(6A): 342-348. https://doi.org/10.11896/jsjkx.201000053
[10] 薛占熬, 孙冰心, 侯昊东, 荆萌萌.
基于多粒度粗糙直觉犹豫模糊集的最优粒度选择方法
Optimal Granulation Selection Method Based on Multi-granulation Rough Intuitionistic Hesitant Fuzzy Sets
计算机科学, 2021, 48(10): 98-106. https://doi.org/10.11896/jsjkx.200800074
[11] 曾惠坤, 米据生, 李仲玲.
形式背景中概念及约简的动态更新方法
Dynamic Updating Method of Concepts and Reduction in Formal Context
计算机科学, 2021, 48(1): 131-135. https://doi.org/10.11896/jsjkx.200800018
[12] 薛占熬, 张敏, 赵丽平, 李永祥.
集对优势关系下多粒度决策粗糙集的可变三支决策模型
Variable Three-way Decision Model of Multi-granulation Decision Rough Sets Under Set-pair Dominance Relation
计算机科学, 2021, 48(1): 157-166. https://doi.org/10.11896/jsjkx.191200175
[13] 桑彬彬, 杨留中, 陈红梅, 王生武.
优势关系粗糙集增量属性约简算法
Incremental Attribute Reduction Algorithm in Dominance-based Rough Set
计算机科学, 2020, 47(8): 137-143. https://doi.org/10.11896/jsjkx.190700188
[14] 陈玉金, 徐吉辉, 史佳辉, 刘宇.
基于直觉犹豫模糊集的三支决策模型及其应用
Three-way Decision Models Based on Intuitionistic Hesitant Fuzzy Sets and Its Applications
计算机科学, 2020, 47(8): 144-150. https://doi.org/10.11896/jsjkx.190800041
[15] 岳晓威, 彭莎, 秦克云.
基于面向对象(属性)概念格的形式背景属性约简方法
Attribute Reduction Methods of Formal Context Based on ObJect (Attribute) Oriented Concept Lattice
计算机科学, 2020, 47(6A): 436-439. https://doi.org/10.11896/JsJkx.191100011
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!