《山东大学学报(理学版)》 ›› 2022, Vol. 57 ›› Issue (9): 33-45.doi: 10.6040/j.issn.1671-9352.0.2021.457
钱进1,2,汤大伟1*,洪承鑫2
QIAN Jin1,2, TANG Da-wei1*, HONG Cheng-xin2
摘要: 现有的知识获取算法所挖掘出的规则太多,不易理解;规则描述太过具体,容易造成过拟合。为此,本文提出了多粒度层次序贯三支决策模型。首先引入概念层次树将目标概念泛化,构建多层次决策表,并设计了多粒度层次序贯三支决策模型,从多视角、多层次计算3个概率区域并获取相应的泛化层次决策规则。最后,通过实验证明了模型的有效性。本模型为知识获取提供了新的视角并丰富了多粒度三支决策的研究。
中图分类号:
[1] ZADEH L A. Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic[J]. Fuzzy Sets and Systems, 1997, 90(2):111-127. [2] 李金海,王飞,吴伟志,等. 基于粒计算的多粒度数据分析方法综述[J]. 数据采集与处理, 2021, 36(3):418-435. LI Jinhai, WANG Fei, WU Weizhi, et al. Review of multi-granularity data analysis methods based on granular computing[J]. Journal of Data Acquisition and Processing, 2021, 36(3):418-435. [3] QIAN Yuhua, LIANG Jiye, YAO Yiyu, et al. MGRS: a multi-granulation rough set[J]. Information Sciences, 2009, 180(6):949-970. [4] QIAN Yuhua, ZHANG Hu, SANG Yanli, et al. Multigranulation decision-theoretic rough sets[J]. International Journal Approximate Reasoning, 2014, 55(1):225-237. [5] 钱进. 多粒度决策粗糙集模型研究[J]. 郑州大学学报(理学版), 2018, 50(1):33-38. QIAN Jin. Research on multigranulation decision-theoretic rough set models[J]. Journal of Zhengzhou University(Natural Science Edition), 2018, 50(1):33-38. [6] 万青,马盈仓,魏玲. 基于多粒度的多源数据知识获取[J]. 山东大学学报(理学版), 2020, 55(1):41-50. WAN Qing, MA Yingcang, WEI Ling. Knowledge acquisition of multi-source data based on multigranularity[J]. Journal of Shangdong University(Natural Science), 2020, 55(1):41-50. [7] 张文娟,李进金,林艺东. 基于图的悲观多粒度粗糙集粒度约简[J]. 山东大学学报(理学版), 2021, 56(1):60-67. ZHANG Wenjuan, LI Jinjin, LIN Yidong. Graph-based granularity reduction in pessimistic multi-granulation rough set[J]. Journal of Shangdong University(Natural Science), 2021, 56(1):60-67. [8] FENG Qinrong, MIAO Duoqian, CHENG Yi. Hierarchical decision rules mining[J]. Expert Systems with Applications, 2010, 37(4):2081-2091. [9] WU Weizhi, LEUNG Yee. Theory and applications of granular labeled partitions in multi-scale decision tables[J]. Information Science, 2011, 181(18):3878-3897. [10] YAO Yiyu. Three-way decisions with probabilistic rough sets[J]. Information Sciences, 2010, 180(3):341-353. [11] YAO Yiyu, DENG Xiaofei. Sequential three-way decisions with probabilistic rough sets[C] //Proceedings of the 10th IEEE International Conference on Cognitive Informatics and Cognitive Computing. Piscataway: IEEE, 2011: 120-125. [12] YAO Yiyu. Tri-level thinking: models of three-way decision[J]. International Journal of Machine Learning and Cybernetics, 2020, 11:947-959. [13] 范琴,刘盾,叶晓庆. 基于序贯三支决策的代价敏感文本情感分析方法[J]. 模式识别与人工智能, 2020, 33(8):732-742. FAN Qin, LIU Dun, YE Xiaoqing. Cost-sensitive text sentiment analysis based on sequential three-way decision[J]. Pattern Recognition and Artificial Intelligence, 2020, 33(8):732-742. [14] 刘琳,魏玲,钱婷. 决策形式背景中具有置信度的三支规则提取[J]. 山东大学学报(理学版), 2017, 52(2):101-110. LIU Lin, WEI Ling, QIAN Ting. Three-way rules extraction in formal decision contexts with confidence[J]. Journal of Shangdong University(Natural Science), 2017, 52(2):101-110. [15] LUO Junfang, HU Mengjun, QIN Keyun. Three-way decision with incomplete information based on similarity and satisfiability[J]. International Journal Approximate Reasoning, 2020, 120:151-183. [16] LI Huaxiong, ZHANG Libo, HUANG Bing, et al. Sequential three-way decision and granulation for cost-sensitive face recognition[J]. Knowledge-Based Systems, 2016, 91:241-251. [17] SAVCHENKO A V. Sequential three-way decisions in multi-category image recognition with deep features based on distance factor[J]. Information Sciences, 2019, 489:18-36. [18] LI Jinhai, HUANG Chenchen, QI Jianjun, et al. Three-way cognitive concept learning via multi-granularity[J]. Information Sciences, 2017, 378(1):244-263. [19] YANG Xin, LI Tianrui, FUJITA Hamido, et al. A unified model of sequential three-way decisions and multilevel incremental processing[J]. Knowledge-Based Systems, 2017, 134(15):172-188. [20] XU Yi, TANG Jingxin, WANG Xusheng. Three sequential multi-class three-way decision models[J]. Information Sciences, 2020, 537:62-90. [21] ZHANG Qinghua, PANG Guohong, WANG Guoyin. A novel sequential three-way decisions model based on penalty function[J]. Knowledge-Based Systems, 2020, 192(15):105350. [22] QIAN Jin, LIU Caihui, MIAO Duoqian, et al. Sequential three-way decisions via multi-granularity[J]. Information Sciences, 2020, 507:606-629. [23] HAO Chen, LI Jinhai, FAN Min, et al. Optimal scale selection in dynamic multi-scale decision tables based on sequential three-way decisions[J]. Information Sciences, 2017, 415/416:213-232. [24] CHENG Yunlong, ZHANG Qinghua, WANG Guoyin, et al. Optimal scale selection and attribute reduction in multi-scale decision tables based on threeway decision[J]. Information Sciences, 2020, 541:36-59. |
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