计算机应用研究2012，Vol.29Issue(9)：3266-3268,3.DOI:10.3969/j.issn.1001-3695.2012.09.017
一种半监督的多标签Boosting分类算法
Semi-supervised multi-label Boosting algorithm
摘要
Abstract
For multi-label classification problem without enough labeled data, this paper proposed a new semi-supervised Boosting algorithm. It provided a semi-supervised general multi-label Boosting framework by using functional gradient descent method. It also used the conditional entropy as a regularization term on unlabeled data in classification model. Experimental result shows that the performance of the new semi-supervised Boosting algorithm can be improved by increasing unlabeled data; it also has a better result than traditional supervised Boosting algorithm by different measures.关键词
Boosting算法/半监督学习/多标签分类Key words
Boosting algorithm/semi-supervised learning/multi-label classification分类
信息技术与安全科学引用本文复制引用
赵晨阳,佀洁..一种半监督的多标签Boosting分类算法[J].计算机应用研究,2012,29(9):3266-3268,3.基金项目
国家自然科学基金资助项目(10771169) （10771169）
