C4.5Bagging algorithm for Chinese text categorization

Aiming at the problem of Chinese text classification,a new method of Bagging is developed.The decision tree C4.5 is selected as the weak classifier and multiple training sets are gained through re-sampling instance.Then,the outputs are combined by voting and the final classification results are obtained.The experimental results show that the classifier based on the C4.5Bagging gets higher precision,recall,F-measure and better performance than C4.5,kNN and Naive-Bayse.