DocumentCode
2924441
Title
Rule induction for tolerance relation-based rough sets
Author
Meng, Jun ; Wang, Peng ; Wang, Xiukun ; Lin, Tsau Young
Author_Institution
Sch. of Comput. Sci. & Technol., Dalian Univ. of Technol., Dalian, China
fYear
2011
fDate
8-10 Nov. 2011
Firstpage
445
Lastpage
450
Abstract
Tolerance relation, derived partition, quotient set and named quotient space are very important concepts based on tolerance relations. In this paper, we review them at first. Then we present the construction of three spaces, namely, granular, quotient and knowledge spaces. We define the concepts of knowledge dependency in rough set models based on tolerance relations, such as weak dependency, strong dependency and central dependency, as well as the relationships among them. We present the process how to obtain the tolerance information table from knowledge base. An example is given to illustrate extracting rules from tolerance information table.
Keywords
data mining; knowledge based systems; rough set theory; derived partition; knowledge base; knowledge dependency; named quotient space; quotient set; rough set models; rule induction; tolerance information table; tolerance relation; Approximation methods; Computed tomography; Data mining; Information systems; Knowledge based systems; Rough sets; Knowledge dependency; Rough set theory; Rule induction; Tolerance relation;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2011 IEEE International Conference on
Conference_Location
Kaohsiung
Print_ISBN
978-1-4577-0372-0
Type
conf
DOI
10.1109/GRC.2011.6122638
Filename
6122638
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