一种基于教学模型的协同训练方法  

A Co-Training Method Based on Teaching-Learning Model

作　　者：胡菊花[1] 姜远[1] 周志华[1] 

机构地区：[1]计算机软件新技术国家重点实验室(南京大学),南京210046

出　　处：《计算机研究与发展》2013年第11期2262-2268,共7页Journal of Computer Research and Development

基　　金：国家自然科学基金项目(60975043;61021062);江苏省自然科学基金项目(BK2011566);深圳市高性能数据挖掘重点实验室开放课题(CXB201005250021A);百度大规模机器学习与数据挖掘主题研究项目(181215P00524)

摘　　要：在很多实际问题中,很容易得到大量未标记数据而较难获取数据的标记;所以半监督学习在过去的10多年中得到了很大的关注.基于不一致性的半监督学习是其中一种十分重要的风范,协同训练是其代表方法.至今为止,大部分协同训练方法在选择未标记示例进行标记时只考虑预测学习器的置信度,而忽视了学习器的需求.受到真实教学系统的启发,提出了一种针对协同训练的教学模型TaLe,其中预测学习器是"教"者,而另一方则为"学"者.进而基于该模型给出了一种新的协同训练方法CoSnT,同时考虑了"教"的置信度和"学"的需求度.实验结果表明CoSnT在收敛效率和泛化性能上都优于标准的协同训练算法.In many real tasks, there are usually abundant unlabeled data but only a few labeled data, and therefore, semi-supervised learning has attracted significant attention in the past few years. Disagreement-based semi-supervised learning approaches are a kind Of state-of-the-art paradigm of semi-supervised learning, where multiple classifiers are generated to label unlabeled instances for each other. Co-training is the first and seminal work in this category. However, during the labeling process, most current co-training style approaches consider only the confidence of the predictor but not any helpfulness for the learner. In this paper, inspired by the real-world teaching-learning system, we propose a teaching-learning model named ＂TaLe＂ for co-training, within which the predictor is considered as a teacher who is teaching while the other is the student who is learning. Based on this model, a new variant of co-training algorithm named CoSnT is presented to consider both the confidence of the teacher and the need of the student. Intuitively, the convergence efficiency of co-training can be improved. Experiments on both multi-view and single-view data sets validate the efficiency and even outperformance of CoSnT over both standard co-training algorithm CoTrain that considers only teacher＇s confidence and CoS algorithm that considers only student＇s need.

关 键 词：半监督学习 基于不一致性 协同训练 TaLe模型 CoSnT “教”置信度 “学”需求度 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]