Abstract Transductive support vector machine (TSVM) is a well-known algorithm that integrates transductive learning into support vector machine. In this paper, a bi-fuzzy progressive transductive support vector machine (BFPTSVM) is constructed by introducing the bi-fuzzy memberships and sample-pruning strategy for the temporary labeled samples. BFPTSVM is capable of degrading the computational complexity and the store memory of TSVM. Simulation results show that BFPTSVM has better classification and convergence performance compared with other learning algorithms.
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2009, Vol. 22 
