Dynamic classifier selection for one-class classification

作者：

Highlights：

• Introduction of dynamic classifier selection for one-class classification.

• Three novel competence measures for one-class classifiers.

• Gaussian approach for extending competence over the entire decision space.

• Results indicating that dynamic selection is a good alternative to static ensembles.

摘要

•Introduction of dynamic classifier selection for one-class classification.•Three novel competence measures for one-class classifiers.•Gaussian approach for extending competence over the entire decision space.•Results indicating that dynamic selection is a good alternative to static ensembles.

论文关键词：One-class classification,Classifier ensemble,Machine learning,Dynamic classifier selection,Competence measure

论文评审过程：Received 3 August 2015, Revised 5 May 2016, Accepted 27 May 2016, Available online 27 May 2016, Version of Record 9 July 2016.

论文官网地址：https://doi.org/10.1016/j.knosys.2016.05.054