Variational inference based bayes online classifiers with concept drift adaptation

作者：

Highlights：

• A novel online classifier based on Bayes variational inference is proposed.

• Two new concept drift adaptation techniques are proposed for the online classifier.

• State-of-the-art performance is achieved for the proposed method.

摘要

•A novel online classifier based on Bayes variational inference is proposed.•Two new concept drift adaptation techniques are proposed for the online classifier.•State-of-the-art performance is achieved for the proposed method.

论文关键词：Online learning,Variational inference,Bayesian classifier,Data stream,Concept drift

论文评审过程：Received 15 November 2017, Revised 7 March 2018, Accepted 8 April 2018, Available online 9 April 2018, Version of Record 18 April 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.04.007