DocumentCode
3291922
Title
An Algorithm for Case-Based Reasoning Based on Similarity Rough Set
Author
Ji, Sai ; Yuan, Shen-Fang ; Wang, Shui-ping
Author_Institution
Dept. of Comput. Sci. & Technol., Nanjing Univ. of Inf. Sci. & Technol., Nanjing
Volume
5
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
226
Lastpage
230
Abstract
A case selection algorithm selects representative cases from a large data set for future case-based reasoning tasks. This paper proposes the SRS algorithm, based on similarity-based rough set theory, which selects a reasonable number of the representative cases while maintaining satisfactory classification accuracy. It also can handle noise and inconsistent data. Experimental results have confirmed the algorithm feasibility and the validity.
Keywords
case-based reasoning; rough set theory; case selection algorithm; case-based reasoning; reasonable number; satisfactory classification accuracy; similarity rough set; Computer science; Databases; Extraterrestrial measurements; Fuzzy systems; Information science; Laboratories; Materials science and technology; Rough sets; Set theory; Space technology;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location
Jinan Shandong
Print_ISBN
978-0-7695-3305-6
Type
conf
DOI
10.1109/FSKD.2008.13
Filename
4666527
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