支持向量机
超参数优化
核(代数)
径向基函数核
计算机科学
选择(遗传算法)
网格
人工智能
核方法
模式识别(心理学)
最小二乘支持向量机
径向基函数
算法
数学优化
数学
人工神经网络
几何学
组合数学
作者
Shunjie Han,Qi Cao,Meng Han
摘要
Kernel function parameter selection is one of the important parts of support vector machine (SVM) modeling. In this paper, we analyzed the features of double linear search method and the grid search method selection method features and the algorithm implementation steps, which consider the selection of RBF kernel function parameter as an example, based on the analysis it is also given the double linear grid search method, and we would get the selection of support vector machines (SVM) nuclear parameter of automatic transmission engineering vehicles by using this method. Experiments show, double linear grid search method sets the advantages which double linear search method of small amount of training and grid search method to learn high precision.
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