A Possibilistic Fuzzy c-Means Clustering Algorithm.

A Possibilistic Fuzzy c-Means Clustering Algorithm.

In 1997, we proposed the fuzzy-possibilistic c-means (FPCM) model and algorithm that generated both membership and typicality values when clustering unlabeled data. FPCM constrains the typicality values so that the sum over all data points of typicalities to a cluster is one. The row sum constraint...

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Detalles Bibliográficos
Publicado en:IEEE Transactions on fuzzy systems 13, 4 (2005).
Autor principal: Pal, N.R
Formato: Artículo
Lenguaje:English
Materias:
Fuzzy rule based system identification.
Large data sets.
Noise sensitivity defect.
Possibilistic fuzzy c-means clustering algorithm.
Unlabeled data clustering.