Generalized eigenvalue proximal support vector regressor for the simultaneous learning of a function and its derivatives

被引:6
|
作者
Khemchandani, Reshma [1 ]
Goyal, Keshav [2 ]
Chandra, Suresh [2 ]
机构
[1] South Asian Univ, Fac Math & Comp Sci, Dept Comp Sci, Delhi, India
[2] Indian Inst Technol, Dept Math, Delhi, India
关键词
Support vector machines; Regression; epsilon-insensitive bound; Generalized eigenvalues; Function approximation; MACHINES;
D O I
10.1007/s13042-017-0687-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Generalized eigenvalue proximal support vector regressor (GEPSVR) determines a pair of epsilon-insensitive bounding regressors by solving a pair of generalized eigenvalue problem. On the lines of GEPSVR, in this paper we propose a novel regressor for the simultaneous learning of a function and its derivatives, termed as GEPSVR of a Function and its Derivatives. The proposed method is fast as it requires the solution of a pair of generalized eigenvalue problems as compared to the solution of a large Quadratic Programming Problem required in other existing approaches. The experiment results on several benchmark functions of more than one variable proves the efficacy of our proposed method.
引用
收藏
页码:2059 / 2070
页数:12
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