NDLI: New heuristic for determination Gaussian kernels parameter

Content Provider	IEEE Xplore Digital Library
Author	Le-Peng Bi Hao Huang Zhi-Yun Zheng Han-Tao Song
Copyright Year	2005
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Beijing Inst. of Technol., China (Le-Peng Bi; Hao Huang; Zhi-Yun Zheng; Han-Tao Song)
Abstract	For SVM using Gaussian kernel, it was known that parameter /spl sigma/ changing from infinity to zero corresponds SVM model performing severe under-fitting to severe over-fitting. In this paper, we theoretically investigated the correspondence between Gaussian kernel's parameter and support vectors' distribution, interesting result was found: with /spl sigma/'s changing from big to small, the samples nearest to other class first become support vectors, then nearest and farthest ones, finally all samples become support vectors. Then we proposed a new heuristic algorithm based on Zhangling et al.'s boundary points theory for selecting Gaussian kernel's parameter. Experimental results showed this heuristic performed well on selecting a suitable a for Gaussian kernel.
Sponsorship	IEEE Syst., Man and Cybernetics Tech. Comm. on Cybernetics, Hong Kong Polytechnic Univ. Hebei Univ. South China Univ. Chongqing Univ. Sun Yat-sen Univ. Harbin Inst. of Technol. and Int. Univ. in Germany
Starting Page	4299
Ending Page	4304
File Size	437785
Page Count	6
File Format	PDF
ISBN	0780390911
DOI	10.1109/ICMLC.2005.1527693
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-08-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Support vector machines Support vector machine classification Quadratic programming Training data Bismuth Computer science Educational institutions Electronic mail H infinity control parameter selection Svm Gaussian kernel support vectors’ distribution
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Parameter selection for Gaussian radial basis function in support vector machine classification

Text Message Authorship Classification Using Kernel Support Vector Machines

Constructing Support Vector Machine Kernels from Orthogonal Polynomials for Face and Speaker Verification

Uncertainty Loom for Early-Warning

Improving SVM on web content classification by document formulation

Two heuristic strategies for searching optimal hyper parameters of C-SVM

Reduction of training datasets via fuzzy entropy for support vector machines

A New Support Vector Machine for Multi-class Classification

Partitionable Kernels for Mapping Kernels

New heuristic for determination Gaussian kernels parameter

Similar Documents

Parameter selection for Gaussian radial basis function in support vector machine classification

Text Message Authorship Classification Using Kernel Support Vector Machines

Constructing Support Vector Machine Kernels from Orthogonal Polynomials for Face and Speaker Verification

Uncertainty Loom for Early-Warning

Improving SVM on web content classification by document formulation

Two heuristic strategies for searching optimal hyper parameters of C-SVM

Reduction of training datasets via fuzzy entropy for support vector machines

A New Support Vector Machine for Multi-class Classification

Partitionable Kernels for Mapping Kernels

New heuristic for determination Gaussian kernels parameter