Journal of Shandong University(Engineering Science) ›› 2021, Vol. 51 ›› Issue (1): 108-113.doi: 10.6040/j.issn.1672-3961.0.2020.248

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Multi-kernel combination method based on rank spatial difference

WANG Mei, XUE Chenglong, ZHANG Qiang   

  1. School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, Heilongjiang, China
  • Online:2021-02-20 Published:2021-03-01

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Abstract: A multi-kernel combination method based on rank spatial difference was proposed in this paper. samples were grouped according to characteristics, different kernel functions are used to train the grouped data, and the parameters of the kernel function are optimized by grid search method. Two kernel functions were selected from the alternative kernel functions, and the data divided into two groups were respectively put into the corresponding kernel function for mapping. Then the rank spatial difference of the data after the kernel function mapping was judged to provide reference for the selection of the basic kernel function. The wine data set, the breast cancer data set and the wine quality data set were selected for the experiment to verify that when the data were mapped by the selected basic kernel function, the greater the rank space difference was, the higher the classification accuracy was. The experimental results showed that the method was feasible for the selection and combination of basic kernel functions.

Key words: multi-kernel learning, rank spatial difference, multi-kernel combination, grid search

CLC Number: 

  • TP391
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