Semi-supervised multi-Layer convolution kernel learning in credit evaluation

作者：

Highlights：

• We analyze the basic solution of a generalized differential operator.

• We give a class of convolution kernel function.

• We propose a semi-supervised multi-layer convolution kernel SVM algorithm.

• We define two semi-supervised methods: SSMCK-MKL and SSMCK-AO.

摘要

•We analyze the basic solution of a generalized differential operator.•We give a class of convolution kernel function.•We propose a semi-supervised multi-layer convolution kernel SVM algorithm.•We define two semi-supervised methods: SSMCK-MKL and SSMCK-AO.

论文关键词：Semi-supervised learning,SVM,Convolution kernel function,Random sampling,Multi-layer kernel

论文评审过程：Received 3 June 2020, Revised 26 April 2021, Accepted 27 May 2021, Available online 29 June 2021, Version of Record 10 July 2021.

论文官网地址：https://doi.org/10.1016/j.patcog.2021.108125