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Mountain and subtractive clustering method: Improvements and generalizations
Author(s) -
Pal Nikhil R.,
Chakraborty Debrup
Publication year - 2000
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/(sici)1098-111x(200004)15:4<329::aid-int5>3.0.co;2-9
Subject(s) - cluster analysis , subtractive color , computer science , data mining , function (biology) , scheme (mathematics) , artificial intelligence , pattern recognition (psychology) , mathematics , algorithm , physics , mathematical analysis , evolutionary biology , optics , biology
The mountain method of clustering and its relative, the subtractive clustering method, are studied here. A scheme to improve the accuracy of the prototypes obtained by the mountain method is proposed. Finally the mountain circular shell method to detect circular shells by using the mountain function is proposed. The proposed method is tested extensively on several synthetic data sets, and the results obtained are quite satisfactory. © 2000 John Wiley & Sons, Inc.