Cart (Loading....) | Create Account
Close category search window
 

Investigation on Different Kernel Functions for Weighted Kernel Regression in Solving Small Sample Problems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Shapiai, M.I. ; Centre of Artificial Intell. & Robot. (CAIRO), Univ. Teknol. Malaysia, Kuala Lumpur, Malaysia ; Sudin, S. ; Ibrahim, Z. ; Khalid, M.

Previously, weighted kernel regression (WKR) has proved to solve small problems. The existing WKR has been successfully solved rational functions with very few samples. The design and development of WKR is important in order to extend the capability of the technique with various kernel functions. Based on WKR, a simple iteration technique is employed to estimate the weight parameters with Gaussian as a kernel function before WKR can be used in predicting the unseen test samples. In this paper, however, we investigate various kernel functions with Particle Swarm Optimization (PSO) as weight estimators as it offers such flexibility in defining the objective function. Hence, PSO has the capability to solve non-closed form solution problem as we also introduce regularization term with L1 norm in defining the objective function as to solve training sample, which corrupted by noise. Through a number of computational experiments, the investigation results show that the prediction quality of WKR is primarily dominated by the smoothing parameter selection rather than the type of kernel function.

Published in:

Computer Modeling and Simulation (EMS), 2011 Fifth UKSim European Symposium on

Date of Conference:

16-18 Nov. 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.