svm-java
Implemented by
Xiaoqian Jiang (xiaoqian@cs.cmu.edu)
Hwanjo Yu (hwanjoyu@postech.ac.kr)
About SVM-JAVA:
SVM-JAVA, developed for research and educational purpose, is a Java implementation of John C. Platt's sequential minimal optimization (SMO) for training a support vector machine (SVM). This program is based on the pseudocode in ``Fast Training of Support Vector Machines using Sequential Minimal Optimization" by John C. Platt and in ``Sequential Minimal Optimization for SVM" by Xianping Ge. It currently supports linear and RBF kernels.
Download svm_java.zip (README)
Using This Code:
This code is publicly available to facilitate research and education in the related areas of data mining and machine learning. If you publish material based on this code, please cite the following reference.
H. Yu and S. Kim, "SVM tutorial: Classification, Regression, and Ranking", Handbook of Natural Computing, p479-506, Springer, 2012.
Bibtex entry:
@MISC{hyu12svm-tutorial,
author = "H. Yu and S. Kim",
title = "{SVM} tutorial: classification, regression, and ranking",
howpublished = "Handbook of Natural Computing, p479-506, Springer",
url = "http://hwanjoyu.org/svm-java/",
year = "2012"
}