Boosting and ensemble learning in Python.
Switch branches/tags
Nothing to show
Clone or download
Pull request Compare This branch is 1 commit behind mblondel:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
benchmarks
examples
ivalice
.gitignore
README.rst
setup.py

README.rst

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 API conventions. Computationally demanding parts are implemented using Numba.

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