One class proximal support vector machines
作者：
Highlights：
• We study the extraction of a target population from a dataset contaminated by outliers.
• To this end, we propose a new Fisher type contrast measure.
• We reconsider this problem from the formalism of proximal support vector machines.
• An approximation of the contrast measure is done using a conjugate gradient method.
• No matrix inversion is needed which lowers the computational complexity.
摘要
Highlights•We study the extraction of a target population from a dataset contaminated by outliers.•To this end, we propose a new Fisher type contrast measure.•We reconsider this problem from the formalism of proximal support vector machines.•An approximation of the contrast measure is done using a conjugate gradient method.•No matrix inversion is needed which lowers the computational complexity.
论文关键词：Outlier detection,Proximal support vector machines,Linear programming problem,Contrast measure
论文评审过程：Received 23 March 2014, Revised 10 April 2015, Accepted 30 September 2015, Available online 22 October 2015, Version of Record 24 December 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.09.036
