By Topic

Selection of kernel parameters for KNN

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
$33 $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

3 Author(s)
Xiao-Yu Qiu ; Shandong Normal University, JiNan, China ; Kai Kang ; Hua-Xiang Zhang

How to choose the optimal parameter is crucial for the kernel method, because kernel parameters perform significantly on the kernel method. In this paper, a novel approach is proposed to choose the kernel parameter for the kernel nearest-neighbor classifier (KNN). The values of the kernel parameter are computed through optimizing an object function designed for measuring the classification reliability of KNN. We test our approach on both artificial and real-word datasets, and the preliminary results demonstrate that our approach provides a practical solution.

Published in:

2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)

Date of Conference:

1-8 June 2008