NDLI: Adapting multiple kernel parameters for support vector machines using genetic algorithms

Content Provider	IEEE Xplore Digital Library
Author	Rojas, S.A. Fernandez-Reyes, D.
Copyright Year	2003
Description	Author affiliation: Div. of Parasitology, Nat. Inst. for Med. Res., London (Rojas, S.A.; Fernandez-Reyes, D.)
Abstract	Kernel parameterization is a key design step in the application of support vector machines (SVM) for supervised learning problems. A grid-search with a cross-validation criteria is often conducted to choose the kernel parameters but it is computationally unfeasible for a large number of them. Here we describe a genetic algorithm (GA) as a method for tuning kernels of multiple parameters for classification tasks, with application to the weighted radial basis function (RBF) kernel. In this type of kernels the number of parameters equals the dimension of the input patterns which is usually high for biological datasets. We show preliminary experimental results where adapted weighted RBF kernels for SVM achieve classification performance over 98% in human serum proteomic profile data. Further improvements to this method may lead to discovery of relevant biomarkers in biomedical applications
Starting Page	626
Ending Page	631
File Size	1032011
Page Count	6
File Format	PDF
ISBN	0780393635
DOI	10.1109/CEC.2005.1554741
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-02
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Support vector machines Genetic algorithms Support vector machine classification Computer science Educational institutions Algorithm design and analysis Application software Supervised learning Grid computing
Content Type	Text
Resource Type	Article

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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
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