Title :
Improved Algorithm for Text Classification Based on TSVM
Author :
Teng, Guifa ; Liu, Yihong ; Ma, Jianbin ; Wang, Fang ; Yao, Huiting
Author_Institution :
Sch. of Inf. Sci. & Technol., Agric. Univ. of Hebei
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
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
Keywords :
classification; learning (artificial intelligence); support vector machines; text analysis; TSVM; double transductive inference algorithm; e-mail classification; text classification; transductive support vector machines; Classification algorithms; Electronic mail; Inference algorithms; Information filtering; Information science; Machine learning algorithms; Support vector machine classification; Support vector machines; Testing; Text categorization;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.298
