document: Efficient training on biased minimax probability machine for imbalanced text classification The Biased Minimax Probability Machine ( BMPM ) constructs a classifier which deals with the imbalanced learning tasks . In this paper , we propose a Second Order Cone Programming ( SOCP ) based algorithm to train the model . We outline the theoretical derivatives of the biased classification model , and address the text classification tasks where negative training documents significantly outnumber the positive ones using the proposed strategy . We evaluated the learning scheme in comparison with traditional solutions on three different datasets . Empirical results have shown that our method is more effective and robust to handle imbalanced text classification problems .
doc_bio_tags: O O O B I I I O O B I O B I I I O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O