NDLI: A New Genetic Folding Algorithm for Regression Problems

Content Provider	IEEE Xplore Digital Library
Author	Mezher, M. Abbod, M.F.
Copyright Year	2012
Abstract	Support Vector Regression (SVR) is an attractive approach for data modeling. The SVR is based on mapping nonlinear input to a linear in the feature space. Instead of minimizing the observed training error, SVR minimizes the generalization error bound using structural risk minimization in combine with a kernel trick control. The model selection plays an important role to the performance of SVR. Therefore, in SVR problems, we attempt to generalize the model by maximizing the margin. Based on experimental results, intelligent model selection is crucial to avoid over fitting and overestimating of generalization capability in such a multidimensional dataset. SVR techniques for choosing the kernel function and additional capacity control is still ongoing research. In this paper, we develop Genetic Folding (GF) for kernel selection of SVR. This methodology was motivated and proofed by our previous published works [4] in classification models. At the end, we have shown comparative results in comparing to predefined kernel models.
Starting Page	46
Ending Page	51
File Size	147036
Page Count	6
File Format	PDF
ISBN	9781467313667
DOI	10.1109/UKSim.2012.107
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-28
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Genetic Folding Evolutionary Algorithm Computational modeling Evolutionary computation Regression Genetics ? -SVR Support Vector Machine Indexes Kernel Biological cells
Content Type	Text
Resource Type	Article

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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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