The nature of statistical learning theory
The nature of statistical learning theory
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Learning with progressive transductive support vector machine
Pattern Recognition Letters
An evolutionary approach to Transduction in Support Vector Machines
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
A continuation method for semi-supervised SVMs
ICML '06 Proceedings of the 23rd international conference on Machine learning
Unconstrained Transductive Support Vector Machines
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
Nonsmooth Optimization Techniques for Semisupervised Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Neural Networks
Hi-index | 12.05 |
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.