DocumentCode
1978548
Title
Dealing with relatively proximity by rough clustering
Author
Hirano, Shoji ; Tsumoto, Shusaku
Author_Institution
Dept. of Med. Inf., Shimane Med. Univ., Japan
fYear
2003
fDate
24-26 July 2003
Firstpage
260
Lastpage
265
Abstract
This paper presents a new clustering method based on the indiscernibility of objects. It provides good partition to objects even when the proximity of objects is defined as relative proximity. The main benefit of this method is that it can be applied to proximity measures that do not satisfy the triangular inequality. Additionally, it may be used with a proximity matrix-thus it does not require direct access to the original data values.
Keywords
fuzzy set theory; pattern clustering; rough set theory; clustering method; indiscernibility-based clustering; objects partition; objects proximity; proximity matrix; proximity measures; relative proximity; rough clustering; triangular inequality; Biomedical informatics; Clustering methods; Euclidean distance; Humans; Linear matrix inequalities; Rough sets;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 2003. NAFIPS 2003. 22nd International Conference of the North American
Print_ISBN
0-7803-7918-7
Type
conf
DOI
10.1109/NAFIPS.2003.1226793
Filename
1226793
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