DocumentCode
2082431
Title
Unsupervised pattern clustering for data mining
Author
Wilamowska, Katarzyna ; Manic, Milos
Author_Institution
Dept. of Comput. Sci., Wyoming Univ., Laramie, WY, USA
Volume
3
fYear
2001
fDate
2001
Firstpage
1862
Abstract
The problem of clustering multidimensional data with similar properties has been targeted in literature. In this paper, the authors have concentrated on the drawback of one of the often used methods, mountain clustering. A method that overcomes this problem is proposed. The method is tested on examples and results are graphically depicted
Keywords
data mining; pattern clustering; unsupervised learning; Kohonen winner-take-all learning; data mining; mountain clustering; multidimensional data clustering; unsupervised pattern clustering; Clustering algorithms; Clustering methods; Computer science; Data analysis; Data mining; Functional analysis; Multidimensional systems; Neurons; Pattern clustering; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics Society, 2001. IECON '01. The 27th Annual Conference of the IEEE
Conference_Location
Denver, CO
Print_ISBN
0-7803-7108-9
Type
conf
DOI
10.1109/IECON.2001.975574
Filename
975574
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