计算机科学 ›› 2019, Vol. 46 ›› Issue (12): 261-265.doi: 10.11896/jsjkx.181102184
郑文彬1,2, 李进金3, 何秋红1,2
ZHENG Wen-bin1,2, LI Jin-jin3, HE Qiu-hong1,2
摘要: 邻域粗糙集理论主要用于知识发现、属性选择、决策分析和数据挖掘等领域,能够根据数据的特点选择合适的离散化策略,在处理模糊和不确定性知识方面表现良好。但是,传统粗糙集属性约简算法存在难以确保获得约简、约简后的粗糙集属性识别准确率低等不足。对此,文中提出了一种基于属性重要度的属性约简算法。在充分考虑现有条件信息熵多方面不足的基础上,借鉴变精度邻域粗糙集理论对阈值参数进行重选,以新的条件信息熵作为度量基准,根据决策信息系统中的偏好属性推导出偏好决策规则集。对偏好决策规则集进行粗糙规则提取,并通过邻域粒化方法建立了变精度邻域粗糙集模型。该模型在处理大规模粗糙集属性数据时,计算时间较长,冗余属性过多。针对该问题,给出了一种属性重要度评价策略,在此基础上通过融合多叉树理论设计了变精度邻域粗糙集属性约简算法。实验结果表明,与传统方法相比,所提算法的属性识别准确率为92%,提高了10%左右,这充分验证了所设计的属性约简算法具有较强的有效性和较高的应用价值。
中图分类号:
[1]WU S Z,LUO Y C,ZHAI J P.A minimum attribute reduction algorithm based on genetic & particle swarm optimization and rough sets[J].Computer Engineering and Science,2016,38(5):1007-1013.(in Chinese) 吴尚智,罗艺纯,翟敬鹏.基于遗传粒子群和粗糙集的最小属性约简算法[J].计算机工程与科学,2016,38(5):1007-1013.[2]AN R M,SUO M L.Application of attributes reduction and weights calculation through neighborhood rough set[J].Computer Engineering and Applications,2016,52(7):160-165.(in Chinese) 安若铭,索明亮.邻域粗糙集在属性约简及权重计算中的应用[J].计算机工程与应用,2016,52(7):160-165.[3]WANG Y L,HUA J J,QIAN W B,et al.Dynamic algorithm of attribute reduction in set-valued decision information system[J].Computer Engineering and Applications,2017,53(17):60-64.(in Chinese) 王映龙,华佳佳,钱文彬,等.集值决策信息系统的动态属性约简算法[J].计算机工程与应用,2017,53(17):60-64.[4]YAO S,WANG J,XU F,et al.Uncertainty measurement and attribute reduction in incomplete neighborhood rough set[J].Journal of Computer Applications,2018,38(1):97-103.(in Chinse) 姚晟,汪杰,徐风,等.不完备邻域粗糙集的不确定性度量和属性约简[J].计算机应用,2018,38(1):97-103.[5]CHANG H Y,MENG Z Q.New Heuristic Algorithm for Attribute Reduction in Decision-theoretic Rough Set[J].Computer Science,2016,43(6):218-222.(in Chinse) 常红岩,蒙祖强.一种新的决策粗糙集启发式属性约简算法[J].计算机科学,2016,43(6):218-222.[6]HONG H J,YE D Y.An Evolutionary Algorithm for Multi-objective Attribute Reduction Involving Optimization of the Number of Decision Rules[J].Journal of Chinese Computer Systems,2016,37(8):1707-1711.(in Chinse) 洪华剑,叶东毅.含规则数优化的多目标属性约简进化算法[J].小型微型计算机系统,2016,37(8):1707-1711.[7]XIONG F,ZHANG X Y.Regional attribute reduction and their structural heuristic algorithms for variable precision rough sets[J].Journal of Computer Applications,2016,36(11):2954-2957.(in Chinse) 熊方,张贤勇.变精度粗糙集的区域属性约简及其结构启发算法[J].计算机应用,2016,36(11):2954-2957.[8]ZHANG Q N,LI D M,XU J,et al.Reduction algorithm for variable precision rough sets[J].Fuzzy Systems and Mathematics,2017(6):132-135.(in Chinse) 张秋娜,李冬梅,徐珺,等.变精度粗糙集的约简算法[J].模糊系统与数学,2017(6):132-135.[9]WANG Y L,ZENG Q,QIAN W B,et al.Attribute reduction algorithm of the incomplete neighborhood decision system with variable precision[J].CAAI Transactions on Intelligent Systems,2017,12(3):386-391.(in Chinse) 王映龙,曾淇,钱文彬,等.变精度下不完备邻域决策系统的属性约简算法[J].智能系统学报,2017,12(3):386-391.[10]ZHU H,DOU H L.Attribute reduction for decision-theory model on the idea of local[J].Electronic Design Engineering,2017,25(21):64-67.(in Chinse) 朱辉,窦慧莉.基于决策粗糙集模型的局部属性约简[J].电子设计工程,2017,25(21):64-67.[11]LIU D J,LI L.Group Evaluation Model of Information Aggregation Based on Attribute Reduction[J].Computer Simulation,2016,33(3):371-375.(in Chinse) 刘东君,李力.基于属性约简的群体评价信息集结模型研究[J].计算机仿真,2016,33(3):371-375.[12]MA F M,CHEN J W,ZHANG T F.Quick attribute reduction algorithm for neighborhood multi-granulation rough set based on double granulate criterion[J].Control & Decision,2017,32(6):1121-1127.[13]LIU Y,XIE H,WANG L,et al.Hyperspectral band selection based on a variable precision neighborhood rough set[J].Applied Optics,2016,55(3):462-481.[14]CHEN D,YANG Y,DONG Z.An incremental algorithm for attribute reduction with variable precision rough sets[J].Applied Soft Computing,2016,45:129-149.[15]CHEN Y,ZENG Z,LU J.Neighborhood rough set reduction with fish swarm algorithm[J].Soft Computing,2016,21(23):1-12.[16]KUMAR S U,INBARANI H H.PSO-based feature selection and neighborhood rough set-based classification for BCI multiclass motor imagery task[J].Neural Computing & Applications,2017,28(11):3239-3258.[17]LIU Y,XIE H,TAN K,et al.Hyperspectral band selection based on consistency-measure of neighborhood rough set theory[J].Measurement Science & Technology,2016,27(5):550-551.[18]PAL U,SHARMISTHA B H,DEBNATH K.R implementation of Bayesian Decision Theoretic Rough Set.Model for Attribute Reduction,2018,22:25-33.[19]WANG X Y,SHEN J L,SHEN Y X,et al.Incomplete Weighted Grade Multi-granulation Rough Set and Granular Reduction.Journal of Chinese Computer Systems,2017,11:141-146.[20]CHEN Y,YANG D.Attribute Reduction Alogrithm Based on Information Entropy and Its Application.Journal of Chongqing University of Technology(Natural Science),2013,27(1):42-46.(in Chinses) 陈媛,杨栋.基于信息熵的属性约简算法及应用.重庆理工大学学报(自然科学),2013,27(1):42-46.[21]CHEN Y,GOU G L,LU L.Improved Algorithm for Attribute Reduction based on Consistency Criterion.Journal of Chongqing University of Technology(Natural Science),2014,28(5):79-83,92.(in Chinses) 陈媛,苟光磊,卢玲.基于一致性准则的属性约简改进算法.重庆理工大学学报(自然科学),2014,28(5):79-83,92. |
[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] | 高荣华, 白强, 王荣, 吴华瑞, 孙想. 改进注意力机制的多叉树网络多作物早期病害识别方法 Multi-tree Network Multi-crop Early Disease Recognition Method Based on Improved Attention Mechanism 计算机科学, 2022, 49(6A): 363-369. https://doi.org/10.11896/jsjkx.210500044 |
[3] | 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 |
[4] | 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 |
[5] | 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 |
[6] | 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 |
[7] | 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 |
[8] | 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 |
[9] | 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 |
[10] | 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 |
[11] | 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 |
[12] | 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 |
[13] | 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 |
[14] | 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 |
[15] | 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 |
|