Regularized least squares support vector regression for the simultaneous learning of a function and its derivatives
Information SciencesPublished 5 May 2008
Jayadeva, Reshma Rastogi, Suresh Chandra
Citations31
SJR quartileQ1
SJR score1.80
SNIP1.98
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TL;DR
A regularized least squares approach based support vector machine for simultaneously approximating a function and its derivatives and the solution of a structured system of linear equations is needed.
Abstract
In this paper, we propose a regularized least squares approach based support vector machine for simultaneously approximating a function and its derivatives. The proposed algorithm is simple and fast as no quadratic programming solver needs to be employed. Effectively, only the solution of a structured system of linear equations is needed.
Keywords
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