Addon to scikit-learn for handling set-based data.
skl-groups is a package to perform machine learning on sets (or “groups”) of features in Python. It extends the scikit-learn 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.
skl-groups is still in fairly early development. The precursor package, 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 (email@example.com) if you’re interested.
Full instructions are in the documentation, 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 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).