Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75281
Title: Reduction of attributes in ordinal decision systems
Authors: Lee, JWT 
Wang, XZ
Wang, JF
Issue Date: 2006
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2006, v. 3930 LNAI, p. 578-587 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: Rough set theory has proven to be a very useful tool in dealing with many decision situations where imprecise and inconsistent information are involved. Recently, there are attempts to extent the use of rough set theory to ordinal decision making in which decisions are made on ordering of objects through assigning them to ordinal categories. Attribute reduction is one of the problems that is studied under such ordinal decision situations. In this paper we examine some of the proposed approaches to find ordinal reducts and present a new perspective and approach to the problem based on ordinal consistency.
Description: 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005, Guangzhou, 18-21 August 2005
URI: http://hdl.handle.net/10397/75281
ISBN: 3540335846
9783540335849
ISSN: 0302-9743
EISSN: 1611-3349
Appears in Collections:Conference Paper

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