Twin minimax probability extreme learning machine for pattern recognition

作者：

Highlights：

• The twin minimax probability extreme learning machine (TMPELM) is proposed.

• TMPELM learns two non-parallel hyperplanes in the feature space for final classification.

• TMPELM utilize the geometric information and statistical information of the samples.

• Numerical results show that TMPELM has better generalization performance.

摘要

•The twin minimax probability extreme learning machine (TMPELM) is proposed.•TMPELM learns two non-parallel hyperplanes in the feature space for final classification.•TMPELM utilize the geometric information and statistical information of the samples.•Numerical results show that TMPELM has better generalization performance.

论文关键词：Minimax probability machine,Twin extreme learning machine,Nonparallel hyperplanes,Second-order cone programming,Pattern recognition

论文评审过程：Received 30 September 2018, Revised 16 June 2019, Accepted 19 June 2019, Available online 21 June 2019, Version of Record 18 November 2019.

论文官网地址：https://doi.org/10.1016/j.knosys.2019.06.014