Guifa Teng, Agricultural University of Hebei, China
Yihong Liu, Agricultural University of Hebei, China
Jianbin Ma, Agricultural University of Hebei, China
Fang Wang, Agricultural University of Hebei, China
TSVM (Transductive Support Vector Machines) tries to minimize misclassification of these particular examples based on a particular test set. It is more practical and performs well on classification. In this paper, a progressive SVM is introduced briefly and an improved algorithm for text classification named double transductive inference algorithm based on TSVM is presented in detail. The experimental results on e-mail classification show that this improved algorithm is effective on a mixed training set of a small number of unlabeled examples and a large number of labeled examples.
Citation:
Guifa Teng, Yihong Liu, Jianbin Ma, Fang Wang, Huiting Yao, "Improved Algorithm for Text Classification Based on TSVM," icicic, vol. 2, pp.55-58, First International Conference on Innovative Computing, Information and Control - Volume II (ICICIC'06), 2006