计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 210700191-5.doi: 10.11896/jsjkx.210700191
徐伟华, 张俊杰, 陈修伟
XU Wei-hua, ZHANG Jun-jie, CHEN Xiu-wei
摘要: 随着大数据时代的到来,数据的结构变得越来越复杂,数据集的维度变得越来越高,这极大地影响了数据挖掘的效率。因此,很有必要进行数据压缩或对信息系统进行属性约简,即去掉不必要的冗余属性,降低数据维度,提高数据挖掘效率。在现实生活中,人们对数据集中每个条件属性的关注度往往是不一样的。首先,在经典模糊决策数据集的基础上,对不同的条件属性进行加权,定义加权得分函数,进一步建立带关注度的模糊序决策信息系统。然后在该系统中引入分布函数,并通过分布可辨识矩阵建立求分布约简的方法。最后,通过案例分析验证了该方法的可行性。
中图分类号:
[1]ZADEH L A.Fuzzy sets[J].Information Control,1965,8(3):338-353. [2]ZADEH L A,GUPTA M M,RAGADE R K,et al.Fuzzy sets and information granularity[M].Amsterdam,1979. [3]TABAKOV M,CHLOPOWIEC A,DLUBAK A.Classificationwith Fuzzification Optimization Combining Fuzzy Information Systems and Type-2 Fuzzy Inference[J].Applied Sciences,2021,11(8):3484. [4]KANZAWA Y,MIYAMOTO S.Generalized Fuzzy c-MeansClustering and its Property of Fuzzy Classification Function[J].Journal of Advanced Computational Intelligence and Intelligent Informatics,2021,25(1):73-82. [5]SANZ J A,BUSTINCE H.A wrapper methodology to learn interval-valued fuzzy rule-based classification systems[J].Applied Soft Computing,2021,104(3):107249. [6]SHEN S,CUI J.Estimation and inference of the fuzzy linear regression model with L fuzzy observations[C]//Fifth International Joint Conference on Computational Sciences & Optimization.IEEE,2012:354-358. [7]KHAMMAR A H,AREFI M,AKBARI M G.A general approach to fuzzy regression models based on different loss functions[J].Soft Computing,2021,25:1-15. [8]SPILIOTISM,GARROTE L.Unit hydrograph identificationbased on fuzzy regression analysis[J].Evolving Systems,2021(8):1-22. [9]CHEN Z,BAGHERINIA A,MINAEI-BIDGOLI B,et al.Fuzzy Clustering Ensemble Considering Cluster Dependability[J].International Journal of Artificial Intelligence Tools,2021,30(2):2150007. [10]FERRAROM B.A class of two-mode clustering algorithms in a fuzzy setting[J].Econometrics and Statistics,2020(18):63-78. [11]GUPTA A,DATTA S,DAS S.Fuzzy Clustering to IdentifyClusters at Different Levels of Fuzziness:An Evolutionary Multiobjective Optimization Approach[J].IEEE Transactions on Cybernetics,2019,51(5):1-11. [12]PAWLAK Z.Rough sets[J].International Journal of Computer &Information Sciences,1982,11(5):341-356. [13]XU W H,ZHANG W X.Distribution Reduction in Inconsistent Information Systems Based on Dominance Relations[J].Fuzzy Systems and Mathematics,2007,21(4):124-131. [14]MI J S,WU W Z,ZHANG W X.Comparative Studies of Know-ledge Reductions in Inconsistent Systems[J].Fuzzy Systems and Mathematics,2003,17(3):54-60. [15]ZHANG W X,MI J S,WU W W.Knowledge Reductions in Inconsistent Information Systems[J].Chinese Journal of Compu-ters,2003,26(1):12-18. [16]XU W H,ZHANG W X.Knowledge Reductions in Inconsistent Information Systems Based on Dominance Relations[J].Computer Science,2006,33(2):182-184. [17]CHEN D,DONG L,MI J.Incremental mechanism of attributereduction based on discernible relations for dynamically increa-sing attribute[J].Soft Computing,2020,24(1):321-332. [18]DONG L,CHEN D.Incremental attribute reduction with rough set for dynamic datasets with simultaneously increasing samples and attributes[J].International Journal of Machine Learning and Cybernetics,2020,11(5):1339-1355. [19]DING W,LIN C T,WITOLD P.Multiple Relevant Feature Ensemble Selection Based on Multilayer Co-Evolutionary Consensus MapReduce[J].IEEE Transactions on Cybernetics,2018,50(2):425-439. [20]DING W,LIN C T,CAO Z.Shared Nearest-Neighbor Quantum Game-Based Attribute Reduction With Hierarchical Coevolutionary Spark and Its Application in Consistent Segmentation of Neonatal Cerebral Cortical Surfaces[J].IEEE Transactions on Neural Networks and Learning Systems,2019,30(7):2013-2027. [21]SANG B,CHEN H,YANG L,et al.Feature selection for dynamic interval-valued ordered data based on fuzzy dominance neighborhood rough set[J],Knowledge-Based System,2021,227,107223. [22]SINGH S,SHREEVASTAVA S,SOM T,et al.A fuzzy simila-rity-based rough set approach for attribute selection in set-va-lued information systems[J].Soft Computing,2020,24(6):4675-4691. [23]SANG B,CHEN H,YANG L,et al.Incremental Feature Selection Using a Conditional Entropy Based on Fuzzy Dominance Neighborhood Rough Sets[J].IEEE Transactions on Fuzzy Systems,2022,30(6):1683-1697. [24]WEN S,BAO Q.Dominance-based rough set approach to incomplete ordered information systems[J].Information Sciences:An International Journal,2016,346:106-129. [25]DAI J H,ZHENG G J,HAN H F,et al.Probability Approach for Interval-valued Ordered Decision Systems in Dominance-based Fuzzy Rough Set Theory[J].Journal of Intelligent & Fuzzy Systems:Applications in Engineering and Technology,2017,32(1):703-710. [26]GUAN L.A heuristic algorithm of attribute reduction in incomplete ordered decision systems[J].Journal of Intelligent & Fuzzy Systems,2019,36(4):3891-3901. [27]DENG S,GUAN S,MIN L I,et al.Decomposition for a newkind of imprecise information system[J].Frontiers of Computer Science(print),2018,12(2):376-395. [28]SUN B,MA W,GONG Z.Dominance-based rough set theoryover interval-valued information systems[J].Expert Systems,2014,31:185-197. |
[1] | 谢健祥, 潘小东, 张波. 基于公理化模糊集合的模糊随机事件及其概率 Fuzzy Random Events and Its Probabilities Based on Axiomatic Fuzzy Sets 计算机科学, 2022, 49(11A): 211100242-7. https://doi.org/10.11896/jsjkx.211100242 |
[2] | 王志强, 郑婷婷, 孙鑫, 李清. 基于一种新的q-rung orthopair模糊交叉熵的属性约简算法 Attribute Reduction Algorithm Based on a New q-rung orthopair Fuzzy Cross Entropy 计算机科学, 2022, 49(11A): 211200142-6. https://doi.org/10.11896/jsjkx.211200142 |
[3] | 戴宗明, 胡凯, 谢捷, 郭亚. 基于直觉模糊集的集成学习算法 Ensemble Learning Algorithm Based on Intuitionistic Fuzzy Sets 计算机科学, 2021, 48(6A): 270-274. https://doi.org/10.11896/jsjkx.200700036 |
[4] | 郑嘉彤, 吴文渊. 基于MLWE的双向可否认加密方案 Practical Bi-deniable Encryption Scheme Based on MLWE 计算机科学, 2021, 48(3): 307-312. https://doi.org/10.11896/jsjkx.200100024 |
[5] | 康波, 潘小东, 王虎. 基于公理化模糊集合的模糊推理方法 Fuzzy Reasoning Method Based on Axiomatic Fuzzy Sets 计算机科学, 2021, 48(11A): 57-62. https://doi.org/10.11896/jsjkx.201200140 |
[6] | 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 |
[7] | 张煜, 陆亿红, 黄德才. 基于密度峰值的加权犹豫模糊聚类算法 Weighted Hesitant Fuzzy Clustering Based on Density Peaks 计算机科学, 2021, 48(1): 145-151. https://doi.org/10.11896/jsjkx.200400043 |
[8] | 胡平, 秦克云. 基于模糊等价的毕达哥拉斯模糊集相似度构造方法 Similarity Construction Method for Pythagorean Fuzzy Set Based on Fuzzy Equivalence 计算机科学, 2021, 48(1): 152-156. https://doi.org/10.11896/jsjkx.191100102 |
[9] | 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 |
[10] | 张梦月, 胡军, 严冠, 李慧嘉. 基于可见性图网络的中国专利申请关注度分析 Analysis of China’s Patent Application Concern Based on Visibility Graph Network 计算机科学, 2020, 47(8): 189-194. https://doi.org/10.11896/jsjkx.200300001 |
[11] | 胡磊, 严丽. 一种基于模糊集和概率分布的不确定XML模型及其代数运算 Uncertain XML Model Based on Fuzzy Sets and Probability Distribution and Its Algebraic Operations 计算机科学, 2020, 47(7): 21-30. https://doi.org/10.11896/jsjkx.190700164 |
[12] | 杨文静,张楠,童向荣,杜贞斌. 基于特定类的区间值决策系统的分布约简 Class-specific Distribution Preservation Reduction in Interval-valued Decision Systems 计算机科学, 2020, 47(3): 92-97. https://doi.org/10.11896/jsjkx.190500180 |
[13] | 杨洁, 王国胤, 张清华, 冯林. 层次粒结构下粗糙模糊集的不确定性度量 Uncertainty Measure of Rough Fuzzy Sets in Hierarchical Granular Structure 计算机科学, 2019, 46(1): 45-50. https://doi.org/10.11896/j.issn.1002-137X.2019.01.007 |
[14] | 郑宏亮, 侯雪辉, 宋笑迎, 庞阔, 邹丽. 基于犹豫模糊可信度的知识推理 Approach for Knowledge Reasoning Based on Hesitate Fuzzy Credibility 计算机科学, 2019, 46(1): 131-137. https://doi.org/10.11896/j.issn.1002-137X.2019.01.020 |
[15] | 吴文华, 宋亚飞, 刘晶. 直觉模糊框架内的证据动态可靠性评估及应用 Dynamic Reliability Evaluation Method of Evidence Based on Intuitionistic Fuzzy Sets and Its Applications 计算机科学, 2018, 45(12): 160-165. https://doi.org/10.11896/j.issn.1002-137X.2018.12.025 |
|