The SVM with uneven margins and Chinese document categorization

We propose and study a new variant of the SVM—the SVM with uneven margins, tailored for document categorisation problems (ie problems where classes are highly unbalanced). Our experiments showed that the new algorithm significantly outperformed the SVM with respect to the document categorisation for small categories. Furthermore, we report the results of the SVM as well as our new algorithm on the Reuters Chinese corpus for document categorisation, which we believe is the first result on this new Chinese corpus.