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skl-groups

skl-groups is a package to perform machine learning on sets (or "groups") of features in Python. It extends the scikit-learn <http://scikit-learn.org>_ library with support for either transforming sets into feature vectors that can be operated on with standard scikit-learn constructs or obtaining pairwise similarity/etc matrices that can be turned into kernels for use in scikit-learn.

For an introduction to the package, why you might want to use it, and how to do so, check out the documentation <https://dougalsutherland.github.io/skl-groups/>_.

skl-groups is still in fairly early development. The precursor package, py-sdm <https://github.com/dougalsutherland/py-sdm/>_, is still somewhat easier to use for some tasks (though it has less functionality and less documentation); skl-groups will hopefully match it in the next few weeks. Feel free to get in touch (dsutherl@cs.cmu.edu) if you're interested.

Installation

Full instructions are in the documentation <https://dougalsutherland.github.io/skl-groups/installation.html>_, but the short version is to do::

$ conda install -c dougal -c r skl-groups

if you use conda, or::

$ pip install skl-groups

if not. If you pip install and want to use the kNN divergence estimator, you'll need to install either cyflann <https://github.com/dougalsutherland/cyflann/>_ or the regular pyflann bindings to FLANN, and you'll want a version of FLANN with OpenMP support.

A much faster version of the kNN estimator is enabled by the skl-groups-accel package, which you can get via::

$ pip install skl-groups-accel

It requires cyflann and a working C compiler with OpenMP support (i.e. gcc, not clang).