The UniverSVM is a SVM implementation written in C/C++. Its functionality comprises large scale transduction via CCCP optimization, sparse solutions via CCCP optimization and data-dependent [...]

The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic interface for SVMs, features several SVM and [...]

Disco is an open-source implementation of the Map-Reduce framework for distributed computing. As the original framework, Disco supports parallel [...]

The SGD package contains a stochastic gradient implementation of linear SVMs and linear CRFs. It demonstrate that a simple stochastic gradient descent is very competitive algorithm for such tasks. [...]

The Sleipnir C++ library implements a variety of machine learning and data manipulation algorithms focusing on heterogeneous data integration and efficiency for large biological data collections.

For modern biology, precise genome annotations are of prime importance as they allow the accurate definition of genic regions. We employ state of the art machine learning methods to assay and [...]

This is a C++ software designed to train large-scale SVMs for binary classification. The algorithm is also implemented in parallel (PGPDT) for distributed memory, strictly coupled multiprocessor [...]

RapidMiner (formerly YALE) is one of the most widely used open-source data mining suites and software solutions due to its leading-edge technologies and its functional range. Applications of [...]

Reference implementation of the LASVM online and active SVM algorithms as described in the JMLR paper. The interesting bit is a small C library that implements the LASVM process and reprocess [...]