计算机科学 ›› 2023, Vol. 50 ›› Issue (6): 92-99.doi: 10.11896/jsjkx.220900037

• 粒计算与知识发现 • 上一篇    下一篇

基于层次聚类的三支决策移动策略

徐怡1,2, 骆帆1, 王敏1   

  1. 1 安徽大学计算机科学与技术学院 合肥 230039
    2 计算智能与信号处理教育部重点实验室(安徽大学) 合肥 230039
  • 收稿日期:2022-09-05 修回日期:2022-12-05 出版日期:2023-06-15 发布日期:2023-06-06
  • 通讯作者: 徐怡(xuyi1023@126.com)
  • 基金资助:
    国家自然科学基金(62076002);安徽省自然科学基金(2008085MF194)

Three-way Decision Movement Strategy Based on Hierarchical Clustering

XU Yi1,2, LUO Fan1, WANG Min1   

  1. 1 College of Computer Science and Technology,Anhui University,Hefei 230039,China
    2 Key Laboratory of Intelligent Computing and Signal Processing,Ministry of Education,Anhui University,Hefei 230039,China
  • Received:2022-09-05 Revised:2022-12-05 Online:2023-06-15 Published:2023-06-06
  • About author:XU Yi,born in 1981,Ph.D,professor,is a member of China Computer Federation.Her main research interests include intelligent information proces-sing,granular computing and edge computing.
  • Supported by:
    National Natural Science Foundation of China(62076002) and Natural Science Foundation of Anhui Province,China(2008085MF194).

摘要: 治略是三支决策TAO模型中的一个重要步骤,是实现对象移动的重要手段。通过实施策略,促使对象从不利区域移动到有利区域。近年来,对于治略方面的研究,学者们提出了两种移动策略,一种是基于区域的移动,另一种是基于对象的移动。然而,这两种移动策略都是从单层次的角度分析和制定移动策略,并未从多层次上考虑移动策略的制定。因此,为了制定多个层次上的移动策略,文中引入层次聚类,提出了一种基于层次聚类的三支决策移动策略模型。首先,使用层次聚类,将不利区域中的对象划分成不同的层次,每一层次上的聚类结果不同。然后,根据全局属性值频率最高准则,为每个层次中的簇制定一个移动策略,不同的簇有不同的移动策略。此外,文中还利用移动过程中产生的收益和代价,对不同层次上的移动策略进行评估。最后,实验结果证明了所提模型的有效性。

关键词: 三支决策, TAO模型, 层次聚类, 移动策略, 多层次

Abstract: Acting is an important step in three-way decision TAO model,and it is also an important method to realize object movement.By implementing the strategies,the object is moved from a disadvantageous area to the advantageous area.In recent years,scholars have proposed two kinds of movement strategies,one is region-based movement,the other is object-based movement.However,the two movement strategies are analyzed and formulated from a single-level perspective,and the formulation of movement strategy is not considered from a multi-level perspective.Therefore,in order to make multi-level movement strategy,this paper introduces hierarchical clustering and proposes a three-way decision movement strategy based on hierarchical clustering.Firstly,it uses hierarchical clustering to divide the objects in the disadvantageous area into different levels,and the clustering results are different at each level.Then,according to the highest frequency of global attribute value criterion,a movement strategy is formulated for clusters in each hierarchy,and different clusters have different movement strategies.In addition,the paper also uses the benefit and cost of the movement process to evaluate the different levels of the movement strategies.Finally,experimental results prove the validity of the proposed model.

Key words: Three-way decision, TAO model, Hierarchical clustering, Movement strategies, Multi-level

中图分类号: 

  • TP301
[1]YAO Y Y.Three-way decisions and cognitive computing[J].Cognitive Computation,2016,8(4):543-554.
[2]YAO Y Y.Three-way decisions with probabilistic rough sets[J].Information Sciences,2010,180(3):341-353.
[3]LIU D,LIANG D C,WANG C C.A novel three-way decision model based on incomplete information system[J].Knowledge-Based Systems,2016,91:32-45.
[4]FANG Y,GAO C,YAO Y Y.Granularity-driven sequentialthree-way decisions:a cost-sensitive approach to classification[J].Information Sciences,2020,507:644-664.
[5]WANG P X,YAO Y Y.CE3:A Three-way Clustering Method Based on Mathematical Morphology[J].Knowledge-Based Systems,2018,155:54-65.
[6]YU H,ZHANG C,WANG G Y.A tree-based incremental overlapping clustering method using the three-way decision theory[J].Knowledge-Based Systems,2016,91:189-203.
[7]YU H,WANG X C,WANG G Y,et al.An active three-wayclustering method via low-rank matrices for multi-view data[J].Information Sciences,2020,507:823-839.
[8]HUANG C C,LI J H,MEI C L,et al.Three-way concept lear-ning based on cognitive operators:An information fusion viewpoint[J].International Journal of Approximate Reasoning,2017,83:218-242.
[9]QI J J,QIAN T,WEI L.Connections between three-way and classical concept lattices[J].Knowledge-Based Systems,2016,91:143-151.
[10]YU H Y,LI Q G,CAI M J.Characteristics of three-way concept lattices and three-way rough concept lattices[J].Knowledge-Based Systems,2018,146:181-189.
[11]LIU D,YE X Q.A matrix factorization based dynamic granula-rity recommendation with three-way decisions[J].Knowledge-Based Systems,2020,191:105243.
[12]ZHANG H R,MIN F.Three-way recommender systems based on random forests[J].Knowledge-Based Systems,2016,91:275-286.
[13]ZHANG H R,MIN F,SHI B.Regression-based three-way recommendation[J].Information Sciences,2017,378:444-461.
[14]FANG Y,MIN F.Cost-sensitive approximate attribute reduction with three-way decisions[J].International Journal of Approximate Reasoning,2019,104:148-165.
[15]MA X A,ZHAO X R.Cost-sensitive three-way class-specific attribute reduction[J].International Journal of Approximate Reasoning,2019,105:153-174.
[16]LIANG D C,WANG M W,XU Z S.Heterogeneous multi-attribute nonadditivity fusion for behavioral three-way decisions in interval type-2 fuzzy environment[J].Information Sciences,2019,496:242-263.
[17]WANG T X,LI H X,ZHOU X Z,et al.A prospect theory-based three-way decision model[J].Knowledge-Based Systems,2020,203:106129.
[18]YANG X,LI T R,FUJITA H,et al.A sequential three-way approach to multi-class decision[J].International Journal of Approximate Reasoning,2019,104:108-125.
[19]QIAN J,LIU C H,MIAO D Q,et al.Sequential three-way decisions via multi-granularity[J].Information Sciences,2020,507:606-629.
[20]LANG G M,LUO J F,YAO Y Y.Three-way conflict analysis:a unification of models based on rough sets and formal concept analysis[J].Knowledge-Based Systems,2020,194:105556.
[21]YAO Y Y.Three-way conflict analysis:reformulations and extensions of the pawlak model[J].Knowledge-Based Systems,2019,180:26-37.
[22]JIANG C M,YAO Y Y.Effectiveness measures in movementbased three-way decisions[J].Knowledge-Based Systems,2018,160:136-143.
[23]GAO C,YAO Y Y.Actionable strategies in three-way decisions[J].Knowledge-Based Systems,2017,133:141-155.
[24]PAWLAK Z.Rough sets[J].International Journal of Computer and Information Sciences,1982,11(5):341-356.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!