On behalf of Andy Mueller, our release manager, I am happy to announce the 0.11 release of scikit-learn.
This release includes some major new features such as randomized sparse models, gradient boosted regression trees, label propagation and many more. The release also has major improvements in the documentation and in stability. Details can be found on the [1]what's new page. We also have a new page with [2]video tutorials on machine learning with scikit-learn and different aspects of the package. Sources and windows binaries are available on sourceforge, through pypi (http://pypi.python.org/pypi/scikit-learn/0.11) or can be installed directly using pip: pip install -U scikit-learn Thanks again to all the contributors who made this release possible. Cheers, Gaël 1. http://scikit-learn.org/stable/whats_new.html 2. http://scikit-learn.org/stable/presentations.html _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
