Leave-Two-Out Cross Validation to optimal shape parameter in radial basis functions

被引：15
|
作者：
Azarboni, Habibe Ramezannezhad [1 ]
Keyanpour, Mohammad [1 ]
Yaghouti, Mohammadreza [1 ]
机构：
[1] Univ Guilan, Fac Math Sci, Rasht, Iran
来源：
ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS | 2019年 / 100卷
关键词：
Radial basis functions; Leave-One-Out Cross Validation; Approximate Moving Least Squares; Shape parameter; Cross validation; PROBABILITY DENSITY-FUNCTION; JUMP-DIFFUSION MODELS; NUMERICAL-SOLUTION; MESHLESS METHOD; INTERPOLATION; ALGORITHM; EQUATION;
D O I：
10.1016/j.enganabound.2018.06.011
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Determination of shape parameter has a major role in the accuracy of the radial basis functions method. In this paper, we present a new method called Leave-Two-Out Cross Validation to determine the best shape parameter. In the proposed method, by deleting two data from the data set, a new formula is derived for determining the error value and then the optimal shape parameter is determined. Num results show that the method will be more accurate in comparison with other methods.
引用
收藏
页码：204 / 210
页数：7
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