期刊文献+

三枝决策粗糙集 被引量:37

Three-way Decision-theoretic Rough Sets
下载PDF
导出
摘要 从贝叶斯理论出发,介绍基于三枝决策粗集理论。首先讨论在期望风险最小决策的语义下决策粗集理论基本模型的构建过程。其次,分析决策粗集三枝决策方法在不同概率区间犯错的可能性,并通过其与二枝决策及Paw-lak粗集三枝决策的差异,给出决策粗集三枝决策方法优于其他两种决策方法的成立条件。最后,提供一种利用决策粗集三枝决策解决实际问题的方法。 A model of three-way decision-theoretic rough sets(DTRS) was presented based on the Bayesian decision theory.Based on the minimum expected risk,a detailed formulation of DTRS was given.Different types of errors in se-veral probability intervals were examined.The conditions under which DTRS three-way method is superior to the Pawlak three-way method and two-way method were identified.DTRS three-way model was discussed for solving the practical decision problems.
出处 《计算机科学》 CSCD 北大核心 2011年第1期246-250,共5页 Computer Science
基金 国家自然科学基金(60873108 70971062) 西南交通大学博士创新基金(200907) 西南交通大学优秀博士论文培育基金(2009LD)资助
关键词 决策粗集理论 贝叶斯过程 三枝决策 二枝决策 Decision-theoretic rough set theory Bayesian decision procedure Three-way decision making Two-way decision making
  • 相关文献

参考文献22

  • 1Pawlak Z. Rough sets [J].International Journal of Computer and Information Sciences, 1982,11:341-356.
  • 2Yao Y Y. Three-way decision: an interpretation of rules in rough set theory[J].LNAI,2009(5589):642- 649.
  • 3Yao Y Y. Three-way decisions with probabilistic rough sets [J]. Information Sciences, 2010,180:341-353.
  • 4Yao Y Y. Two semantic issues in a probabilistie rough set model [J]. Fundamenta Informatieae, Manuscript, 2009.
  • 5Pawlak Z,Wong S K M, Ziarko W. Rough sets: probabilistic versus deterministic approach[J].Inter. Journal of Man-Machine Studies, 1988,29 : 81-95.
  • 6Yao Y Y,Wong S K M. A decision theoretic framework for ap proximating concepts[J].Inter. Journal of Man-machine Stu dies, 1992,37 : 793-809.
  • 7Yao Y Y. Decision-theoretic rough set models [J]. Locture Notes in Artificial Intelligence,2007(4481) : 1-12.
  • 8Ziarko W. Variable precision rough set model [J]. Journal of Computer and System Sciences, 1993,46 : 39-59.
  • 9Slezak D, Rough sets and Bayes factor [J].LNCS Transactions on Rough Sets III, 2005 : 202 -229.
  • 10Slezak D,Ziarko W. The investigation of the Bayesian rough set model[J]. International Jounral of Approximate Reasoning, 2005,40:81-91.

二级参考文献8

  • 1Skowron A,Son N.Boolean reasoning scheme with some applications in data mining[C]//LNAI 1704:Discovery PKDD'99,Prague,Czech Republic.Berlin:Springer Verlag,1999:107-115.
  • 2Sahami M.A Bayesian approach to filtering junk E-mail[C]//Learning for Text Categorization:Papers from the 1998 Workshop.AAAI Technical Report WS-98-05,1998.
  • 3Cristianini N.An introduction to Support Vector Machines and other kernel-based learning methods[M].Cambridge:Cambridge University Press,2002.
  • 4Yao Y Y,Wong S K M.A decision-theoretic framework for approximating concepts[J].International Journal of Man-machine Studies,1992,37 (6):793-809.
  • 5Yao Y Y.Information granulation and approximation in a decisiontheoretic model of rough sets,rough-neuro computing:a way to computing with words[M].Heidelberg:Physica-Verlag,2002.
  • 6Pawlak Z.Rough sets[J].International Journal of Computer and Information Sciences,1982,11:341-356.
  • 7Pal S,Skowron A.Rough fuzzy hybridization:a new trend in decision-making[M].[S.l.]:Springer,1999.
  • 8Aleksander H.Discernibility and rough sets in medicine[D].Norway:Department of Computer and Information Science,Norwegian University of Science and Technology,1999.

共引文献14

同被引文献274

引证文献37

二级引证文献164

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部