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http://hdl.handle.net/10071/10583
acessibilidade
Title: A convex semi-nonnegative matrix factorisation approach to fuzzy c-means clustering
Authors: Suleman, A.
Keywords: Fuzzy clustering
Fuzzy c-means
Semi-nonnegative matrix factorisation
Principal component analysis
Issue Date: 2015
Publisher: Elsevier
Abstract: We propose an alternative approach to fuzzy c-means clustering which eliminates the weighting exponent parameter of conventional algorithms. It is based on a particular convex factorisation of data matrix. The proposed method is invariant under certain linear transformations of the data including principal component analysis. We tested its accuracy using both synthetic data and real datasets, and compared it to that provided by the usual fuzzy c-means algorithm. We were able to ascertain that our proposal can be a credible yet easier alternative to this approach to fuzzy clustering. Moreover, it showed no noticeable sensitivity to the initial guess of the partition matrix.
Peer reviewed: yes
URI: http://hdl.handle.net/10071/10583
DOI: 10.1016/j.fss.2014.07.021
ISSN: 0165-0114
Ciência-IUL: https://ciencia.iscte-iul.pt/id/ci-pub-25989
Accession number: WOS:000352208900005
Appears in Collections:DINÂMIA'CET-RI - Artigo em revista científica internacional com arbitragem científica

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