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Survey of Kernel Extreme Learning Machine Kernel Function Based on the Perspective of Kernel Parameter Optimization Time

机译:基于内核参数优化时间的内核极限学习机内核功能调查

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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.
机译:内核极限学习机(KELM)越来越广泛地应用于各个领域,而决定KELM性能的因素是所选择的内核功能。本文将内核函数分为两种常见类型:内核内积函数和基于正交多项式的内核函数,这些多项式仅需要自然数的值。从核参数优化时间的角度,系统地总结了上述核函数的研究现状和发展,为相关研究人员提供了发展方向和研究方向的最新成果。

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