Shogun Machine Learning Toolbox (Technical University Berlin / Max Planck Campus Tübingen)
List of projects accepted into Shogun Machine Learning Toolbox (Technical University Berlin / Max Planck Campus Tübingen)
SHOGUN is a machine learning toolbox, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers a considerable number of machine learning models such as support vector machines for classification and regression, hidden Markov models, multiple kernel learning, linear discriminant analysis, linear programming machines, and perceptrons. Most of the specific algorithms are able to deal with several different data classes, including dense and sparse vectors and sequences using floating point or discrete data types. We have used this toolbox in several applications from computational biology, some of them coming with no less than 10 million training examples and others with 7 billion test examples. With more than a thousand installations worldwide, SHOGUN is already widely adopted in the machine learning community and beyond.
SHOGUN is implemented in C++ and interfaces to MATLAB, R, Octave, Python, and has a stand-alone command line interface. The source code is freely available under the GNU General Public License, Version 3 at http://www.shogun-toolbox.org.
This summer we are looking to extend the library in four different ways: Improving interfaces to other machine learning libraries or integrating them when appropriate, improved i/o support, framework improvements and new machine algorithms. Here is listed a set of suggestions for projects.
Please use the scheme shown below for your student application. If you have any questions, ask on the mailing list (firstname.lastname@example.org, please note that you have to be subscribed in order to post).
Now google summer of code is over with a big success for shogun: All students completed their projects successfully and their source code has been merged into core shogun. In addition to shogun's github page https://github.com/shogun-toolbox/shogun/ , the students code contributions can be found in http://code.google.com/p/google-summer-of-code-2011-shogun-machine-learning-toolbox/ .