DocumentCode :
1126786
Title :
Approximate clustering via the mountain method
Author :
Yager, Ronald R. ; Filev, Dimitar P.
Author_Institution :
Machine Intelligence Inst., Iona Coll., New Rochelle, NY, USA
Volume :
24
Issue :
8
fYear :
1994
fDate :
8/1/1994 12:00:00 AM
Firstpage :
1279
Lastpage :
1284
Abstract :
We develop a simple and effective approach for approximate estimation of the cluster centers on the basis of the concept of a mountain function. We call the procedure the mountain method. It can be useful for obtaining the initial values of the clusters that are required by more complex cluster algorithms. It also can be used as a stand alone simple approximate clustering technique. The method is based upon a griding on the space, the construction of a mountain function from the data and then a destruction of the mountains to obtain the cluster centers
Keywords :
approximation theory; fuzzy set theory; optimisation; pattern recognition; approximate clustering; cluster center location; fuzzy clustering; heuristic algorithm; mountain method; space griding; Calibration; Machine vision; Metrology; Mobile robots; Motion estimation; Navigation; Pattern matching; Robot vision systems; Robotics and automation; Stereo vision;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/21.299710
Filename :
299710
Link To Document :
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