SVMlin http://mloss.orgUpdates and additions to SVMlin enTue, 27 Nov 2007 08:04:48 -0000SVMlin 1.0<html><p>SVMlin: Fast Linear SVMs for Supervised and Semi-supervised Learning </p> <p>SVMlin is software package for linear SVMs. It is well-suited to classification problems involving a large number of examples and features. It is primarily written for sparse datasets (number of non-zero features in an example is typically small). It is written in C/C++. A mex wrapper is available for MATLAB users. </p> <p>SVMlin can also utilize unlabeled data, in addition to labeled examples. It currently implements two extensions of standard SVMs to incorporate unlabeled examples. </p> <p>SVMlin (version 1.0) implements the following algorithms: </p> <p>Fully supervised (using only labeled examples) </p> <ul> <li><p>Linear Regularized Least Squares (RLS) Classification<br /> </p> </li> <li><p>Modified Finite Newton Linear L2-SVMs (Keerthi and DeCoste, JMLR, 2005) </p> </li> </ul> <p>Semi-supervised (Large Scale Semi-supervised Linear SVMs, Keerthi and Sindhwani, SIGIR 2006) </p> <ul> <li><p>Multi-switch linear Transductive L2-SVMs </p> </li> <li><p>Deterministic Annealing (DA) for Semi-supervised Linear L2-SVMs </p> </li> </ul></html>Vikas Sindhwani Tue, 27 Nov 2007 08:04:48 -0000 supervised learninglinear svm