lightning is a library for large-scale linear classification, regression and ranking in Python.

Highlights:

• follows the scikit-learn API conventions
• supports natively both dense and sparse data representations
• computationally demanding parts implemented in Cython

Solvers supported:

• primal coordinate descent
• dual coordinate descent (SDCA, Prox-SDCA)
• SGD, AdaGrad, SAG, SAGA, SVRG
• FISTA

Example that shows how to learn a multiclass classifier with group lasso penalty on the News20 dataset (c.f., Blondel et al. 2013):

from sklearn.datasets import fetch_20newsgroups_vectorized
from lightning.classification import CDClassifier
# Load News20 dataset from scikit-learn.
bunch = fetch_20newsgroups_vectorized(subset="all")
X = bunch.data
y = bunch.target
# Set classifier options.
clf = CDClassifier(penalty="l1/l2",
 loss="squared_hinge",
 multiclass=True,
 max_iter=20,
 alpha=1e-4,
 C=1.0 / X.shape[0],
 tol=1e-3)
# Train the model.
clf.fit(X, y)
# Accuracy
print(clf.score(X, y))
# Percentage of selected features
print(clf.n_nonzero(percentage=True))

lightning requires Python >= 2.7, setuptools, Numpy >= 1.3, SciPy >= 0.7 and scikit-learn >= 0.15. Building from source also requires Cython and a working C/C++ compiler. To run the tests you will also need nose >= 0.10.

Precompiled binaries for the stable version of lightning are available for the main platforms and can be installed using pip:

pip install sklearn-contrib-lightning

or conda:

conda install -c conda-forge sklearn-contrib-lightning

The development version of lightning can be installed from its git repository. In this case it is assumed that you have the git version control system, a working C++ compiler, Cython and the numpy development libraries. In order to install the development version, type:

git clone https://github.com/scikit-learn-contrib/lightning.git
cd lightning
python setup.py build
sudo python setup.py install

http://contrib.scikit-learn.org/lightning/

https://github.com/scikit-learn-contrib/lightning

If you use this software, please cite it. Here is a BibTex snippet that you can use:

@misc{lightning_2016,
 author = {Blondel, Mathieu and
 Pedregosa, Fabian},
 title = {{Lightning: large-scale linear classification,
 regression and ranking in Python}},
 year = 2016,
 doi = {10.5281/zenodo.200504},
 url = {https://doi.org/10.5281/zenodo.200504}
}

Other citing formats are available in its Zenodo entry .

• Mathieu Blondel, 2012-present
• Manoj Kumar, 2015-present
• Arnaud Rachez, 2016-present
• Fabian Pedregosa, 2016-present