关键词: 迁移学习,支持向量机,分类

Abstract: Transfer learning method is a new machine learning framework,which aims at realizing an effective learning for target domain by efficiently transferring the existing knowledge from source domain to target domain.It would be nice to reduce the need and effort to recollect the training data.However,the classifier trained by the data of source domain and target domain often put in a worse performance than the classifier only trained by the data of target domain,which leads to the appearance of “negative transfer”.To address this problem,a safety-control mechanism with the knowledge of the labeled data of target domain was proposed for safe transfer leaning.Furthermore,in implementation,based on a recent transfer learning method (TL-SVM),a safety-aware transfer learning support vector machine(STL-SVM) was proposed,which avoids the appearance of “negative transfer” of TL-SVM theoretically.Experiment results on artificial datasets and real-world datasets show the effectiveness of the proposed method.

Key words: Transfer learning,Support vector machine,Classification