An innovative one-class least squares support vector machine model based on continuous cognition

作者：

Highlights：

• This paper proposed a new framework of one-class classification based on continuous cognition.

• The framework is implemented with LSSVM and the corresponding classifier is called OC-LSSVM.

• Several simulation and real datasets are used to test the performance of OC-LSSVM.

• OC-LSSVM shows state-of-the-art performance compared to established methods.

摘要

•This paper proposed a new framework of one-class classification based on continuous cognition.•The framework is implemented with LSSVM and the corresponding classifier is called OC-LSSVM.•Several simulation and real datasets are used to test the performance of OC-LSSVM.•OC-LSSVM shows state-of-the-art performance compared to established methods.

论文关键词：Continuous cognition,Multiple regression,One-class classification,Least squares support vector machine

论文评审过程：Received 16 August 2016, Revised 5 February 2017, Accepted 20 February 2017, Available online 21 February 2017, Version of Record 27 March 2017.

论文官网地址：https://doi.org/10.1016/j.knosys.2017.02.024