No Detail Found!

Smooth support vector regression based on modification spline interpolation.

Author(s)
Bin Ren School of Electronic Engineering, Dongguan University of Technology, Dongguan, 523808, China
Huijie Liu School of Electronic Engineering, Dongguan University of Technology, Dongguan, 523808, China
Lei Yang School of Electronic Engineering, Dongguan University of Technology, Dongguan, 523808, China
Lianglun Cheng School of Automation, Guangdong University of Technology, Guangzhou, 510006, China
Abstract
Regression analysis is often formulated as an optimization problem with squared loss functions. Facing the challenge of the selection of the proper function class with polynomial smooth techniques applied to Support Vector Regression models, this study takes three interplation points spline interpolation technology and modification interpolation value to generate a new polynomial smooth function x |2 e in e –insensitive support vector regression. The experimental analysis shows that S2Me -function is better than p2e–function and S2e -function in properties, and the approximation accuracy of the proposed smooth function is three order of higher than that of classical p2e-function.
Publication Details
Page(s) 92-100
DOI DOI not available
Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 44, Issue: 1, Year: 2012

Request the full text from PASTIC

More from Journal of Theoretical and Applied Information Technology
0

Citations

0

Downloads

28

Views

Copyright ©  PASTIC National Center, Islamabad www.pastic.gov.pk