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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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Publication date:
2009-01-01
URN:
uuid:e823a3ee-3672-42d9-86be-2a985a8cd4fc
Local pid:
oai:eprints.maths.ox.ac.uk:953

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