Survey of Kernel Extreme Learning Machine Kernel Function Based on the Perspective of Kernel Parameter Optimization Time
作者
Senyue Zhang,Tan Wen-An,Yibo Li
出处
期刊:2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)日期:2018-04-01卷期号:34: 430-433被引量:1
标识
DOI:10.1109/icnisc.2018.00093
摘要
The Kernel Extreme Learning Machine (KELM) is more and more widely used in various fields, and the factor that determines the performance of KELM is the selected kernel function. The kernel functions are divided into two common types in this paper: the kernel inner product functions and kernel functions based on orthogonal polynomials that only require values in natural numbers. From the perspective of kernel parameter optimization time, the current research status and development of the above kernel functions are systematically summarized, which provided relevant researchers with the development history and latest results of the research direction.