计算机工程与应用2016，Vol.52Issue(14)：156-160,5.DOI:10.3778/j.issn.1002-8331.1601-0166
一种获取标签相关信息的多标签分类方法
Novel multi-label classification method by acquiring label relevant informa-tion
摘要
Abstract
Multi-label classification methods have been applied in many real-world fields. To the problem of label-relevance in multi-label classification, this paper proposes a novel multi-label classification method by automatically acquiring label relevant information. The method introduces a probabilistic model to solve the established optimization sub-problem by using alternative maximization algorithm. It also gives the inference. This model can acquire label relevant information, and it can achieve better multi-label classification results. The experimental results on four real multi-label datasets show that the proposed method can achieve higher classification and prediction evaluation values and several other measure index values than the existing multi-label classification methods.关键词
多标签分类/标签关联信息/概率模型/交替最大化算法Key words
multi-label classification/label relevant information/probabilistic model/alternative maximization algorithm分类
信息技术与安全科学引用本文复制引用
郑伦川,邓亚平..一种获取标签相关信息的多标签分类方法[J].计算机工程与应用,2016,52(14):156-160,5.基金项目
国家自然科学基金（No.61275473）；重庆市教委2014年重点项目（No.142082）。 （）
