Multi-Label Classification via Manipulating Labels

摘要：

　　Unlike traditional classification problem,multi-label learning task is to predict a label set with unknown size for an example.While the exponential number of possible label sets challenges the task of multi-label learning.Many approaches by manipulating labels have been proposed.In this paper,we propose a new method via manipulating labels for multi-Label Learning:adding a virtual label to the original label set,appending tbe label subset selected by mutual information for each pairwise labels to the original feature set,and finally learning a binary classifier for each pairwise labels.Extensive experiments show that,compared with advanced multi-label methods,the proposed method induces models with significantly better performance..

关键词： multi-label mutual information pairwise labels

作者: Huaping Guo Ming Fan

作者单位: School of Information Engineering,ZhengZhou University,P.R.China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 974-977

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）