Soeren Sonnenburg: Shogun Toolbox Version 3.0 released!
Dear all,
we are proud to announce the 3.0 release of the Shogun Machine-Learning Toolbox. This release features the incredible projects of our 8 hard-working Google Summer of Code students. In addition, you get other cool new features as well as lots of internal improvements, bugfixes, and documentation improvements. To speak in numbers, we got more than 2000 commits changing almost 400000 lines in more than 7000 files and increased the number of unit tests from 50 to 600. This is the largest release that Shogun ever had! Please visit http://shogun-toolbox.org/ to obtain Shogun.
News
Here is a brief description of what is new, starting with the GSoC projects, which deserve most fame:
- Gaussian Process classification by Roman Votjakov
- Structured Output Learning of graph models by Shell Hu
- Estimators for log-determinants of large sparse matrices by Soumyajit De
- Feature Hashing and random kitchen sinks by Evangelos Anagnostopoulos
- Independent Component Analysis by Kevin Hughes
- A web-based demo framework by Liu Zhengyang
- Metric learning with large margin nearest neighbours by Fernando Iglesias
- Native support for various popular file formats by Evgeniy Andreev