DocumentCode :
2542234
Title :
A fuzzy clustering model of data with proportional membership
Author :
Nascimento, S. ; Mirkin, B. ; Moura-Pires, F.
Author_Institution :
Fac. Ciencias e Technol., Univ. Nova de Lisboa, Portugal
fYear :
2000
fDate :
2000
Firstpage :
261
Lastpage :
266
Abstract :
The fuzzy clustering proportional membership (FCPM) proposes a model of how data are generated from a cluster structure to be identified. Cluster prototypes and membership functions are meaningful in the context of the model. In particular, the membership of an entity to a cluster expresses the proportion of the cluster´s prototype reflected in the entity (proportional membership). We explore the notion of proportional membership and compare it against the fuzzy c-means (FCM) distance membership. The ability of FCPM to reveal the underlying clustering model of data has been studied and a comparison with FCM had also been performed
Keywords :
fuzzy logic; fuzzy set theory; pattern clustering; cluster prototypes; data; fuzzy c-means distance membership; fuzzy clustering model; fuzzy clustering proportional membership; Computer science; Context modeling; Educational institutions; Equations; Fuzzy sets; Gravity; Informatics; Prototypes;
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.2000.877433
Filename :
877433
Link To Document :
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