DocumentCode
2541727
Title
Fuzzy clustering with outliers
Author
Keller, Annette
Author_Institution
German Aerosp. Center, Braunschweig, Germany
fYear
2000
fDate
2000
Firstpage
143
Lastpage
147
Abstract
In this paper we introduce a modified objective function for fuzzy clustering. We add an additional weighting factor for each datum and derive necessary conditions for the introduced parameter in order to optimise the objective function. These conditions are used in an alternating optimisation scheme to calculate a partition of sample data. The obtained weights determine a kind of representativeness of each datum for the data distribution. They can be used to identify outliers and enable the expert to locate critical areas that are often represented by only a few outliers
Keywords
fuzzy set theory; pattern clustering; fuzzy clustering; modified objective function; outliers; weighting factor; Clustering algorithms; Equations; Euclidean distance; Fuzzy sets; Noise robustness; Prototypes; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 2000. NAFIPS. 19th International Conference of the North American
Conference_Location
Atlanta, GA
Print_ISBN
0-7803-6274-8
Type
conf
DOI
10.1109/NAFIPS.2000.877408
Filename
877408
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