An Ensemble Method for Multi-class and Multi-label Text Categorization
Bofeng Zhang, Xin Xu, Jinshu Su · 2007
A method for multi-class and multi-label automated text categorization based on twin-SVM with naïve Bayes ensemble is proposed.Twin-SVM classifiers give a solution to the multi-label problem.For multiclass situation, naïve Bayes classifier constrains the belonging scope of a testing sample within a few most likely classes and greatly reduces the number of binary classifiers needed to make the final prediction.The benefits of the ensemble method are described and preliminary results with Reuters-21578 data set are also presented.