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DifFUZZY: A fuzzy spectral clustering algorithm for complex data sets

Abstract:

Motivation: Soft (fuzzy) clustering techniques are often used in the study of high-dimensional data sets, such as microarray and other high-throughput bioinformatics data. The most widely used method is the Fuzzy C-means algorithm (FCM), but it can present difficulties when dealing with some data sets. Results: A spectral fuzzy clustering algorithm, DifFUZZY, applicable to a larger class of clustering problems than other fuzzy clustering algorithms is developed. Examples of data sets (synth...

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Ornella Cominetti More by this author
Anastasios Matzavinos More by this author
Sandhya Samarasinghe More by this author
Don Kulasiri More by this author
Philip K. Maini More by this author
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Publication date:
2009
URN:
uuid:e823a3ee-3672-42d9-86be-2a985a8cd4fc
Local pid:
oai:eprints.maths.ox.ac.uk:953

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