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A bi-fuzzy progressive transductive support vector machine (BFPTSVM) algorithm
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DOI：10.1016/j.eswa.2009.05.099.png)
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Abstract
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Transductive support vector machine (TSVM) is a well-known algorithm that realizes transductive learning in the field of support vector classification. This paper constructs a bi-fuzzy progressive transductive support vector machine (BFPTSVM) algorithm by combining the proposed notation of bi-fuzzy memberships for the temporary labeled sample appeared in progressive learning process and the sample-pruning strategy, which decreases the computation complexity and store memory of algorithm. Simulation experiments show that the BFPTSVM algorithm derives better classification performance and converges rapidly with better stability compared to the other learning algorithms. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.
Keywords:
Support vector machine
Transductive learning
Bi-fuzzy memberships
Bi-fuzzy support vector machine
Sample-pruning strategy
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