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
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;
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
DOI :
10.1109/FSKD.2008.13
