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ivalice

Boosting and ensemble learning library in Python.

Algorithms supported:

• Classification and regression trees (work in progress)
• Random forests (work in progress)
• Gradient Boosting
• McRank
• LambdaMART

ivalice follows the scikit-learn <http://scikit-learn.org>_ API conventions. Computationally demanding parts are implemented using Numba <http://numba.pydata.org>_.

Dependencies

ivalice needs Python >= 2.7, setuptools, Numpy >= 1.3, SciPy >= 0.7, scikit-learn >= 0.15.1 and Numba >= 0.13.4.

To run the tests you will also need nose >= 0.10.

Installation

To install ivalice from pip, type::

pip install https://github.com/mblondel/ivalice/archive/master.zip

To install ivalice from source, type::

git clone https://github.com/mblondel/ivalice.git cd ivalice sudo python setup.py install

On Github

https://github.com/mblondel/ivalice

Author

Mathieu Blondel, 2014-present