VRIFA: A Nonlinear SVM Visualization Tool using Nomogram and Localized Radial Basis Function (LRBF) Kernels

posted Sep 12, 2009 7:15 AM by Taehoon Kim [ updated Apr 21, 2011 3:43 PM ]

Implemented by

Ngo Anh Vien (vienna@khu.ac.kr)
Nguyen Hoang Viet (vietict@khu.ac.kr)
Hwanjo Yu (hwanjoyu@postech.ac.kr)

About VRIFA:

VRIFA, written in C#.NET, is a nonlinear SVM visualization tool using nomogram and localized radial basis function (LRBF) kernels. It is implemented based on the paper, " Nonlinear Support Vector Machine Visualization for Risk Factor Analysis using Nomograms and Localized Radial Basis Function Kernels" by Baek Hwan Cho, et. al, and " .NET conversion of LIBSVM" by Matthew Johnson. It currently supports linear and LRBF kernels.
Download vrifa.zip (README)

Using VRIFA:

This tool is publicly available to facilitate research and education in the related areas of data mining, machine learning, and medical informatics. If you publish material based on this tool, please refer to the source as follows, to help others to obtain the same tool and reproduce your experiments.

N. A. Vien, N. H. Viet and H. Yu. VRIFA: A nonlinear SVM visualization tool using nomogram and localized radial basis function (LRBF) kernels. Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), http://dm.postech.ac.kr/vrifa, 2008.

Bibtex entry:
@MISC{POSTECH08VRIFA,
author = "N. A. Vien and N. H. Viet and H. Yu",
title = "{VRIFA}: A nonlinear SVM visualization tool using nomogram and localized radial basis function (LRBF) kernels",
howpublished = "http://dm.postech.ac.kr/vrifa",
year = "2008"
}

v.4

README.txt

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Taehoon Kim,

Sep 12, 2009 7:16 AM

v.4

vrifa.zip

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Taehoon Kim,

Sep 12, 2009 7:16 AM

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VRIFA: A Nonlinear SVM Visualization Tool using Nomogram and Localized Radial Basis Function (LRBF) Kernels