Some courses which have used libsvm as a tool.Q2:_Installation_and_running_the_program(12).Automatic model selection which can generate contour of cross validation accuracy.It's also included in some data mining environments:, and. demonstrating SVM classification and regression.Various kernels (including precomputed kernel matrix).LIBSVM provides a simple interface where users can easily link it with their own programs. () Our goal is to help users from other fields to easily use SVM as a tool. Journal of Machine Learning Research 6, 1889-1918, 2005. Since version 2.8, it implements an SMO-type algorithm proposed in this paper: R.-E. Introduction LIBSVM is an integrated software for support vector classification, (C-SVC, ), regression (epsilon-SVR, ) and distribution estimation (). Using libsvm, our group is the winner of IJCNN 2001 Challenge (two of the three competitions), EUNITE world wide competition on electricity load prediction, (third place), (one of the two winners), and 2010 (2nd place). To see the importance of parameter selection, please see our for beginners. To use this tool, you also need to install and. The parameter selection tool grid.py generates the following contour of cross-validation accuracy. It makes everything automatic-from data scaling to parameter selection. Is available now! (mainly written for beginners) We now have an easy script (easy.py) for users who know NOTHING about SVM. We now have a nice page providing problems in LIBSVM format. Please check it if you need some functions not supported in LIBSVM. LIBSVM - A Library for Support Vector Machines LIBSVM - A Library for Support Vector Machines Chih-Chung Chang and Version 3.23 released on July 15, 2018.
Instructions for using LIBSVM are in the README files in the main directory and some sub-directories. Otherwise, you might consider downloading the source code from the LIBSVM authors' page and compiling and installing it per their instructions.
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