scikit-hubness 0.21.0

This is the first major release of scikit-hubness.

The package is organized as follows:

• skhubness.analysis provides the Hubness class, with which you can analyse your data for the presence and extent of hubness.
  For example, you can assess the skewness of the k-occurrence distribution, or its Robin Hood index.
• skhubness.neighbors provides exact and approximate nearest neighbor search, with or without hubness reduction. The package acts as a drop-in replacement for sklearn.neighbors. You will find all its estimators, classes, and functions plus ANN and hubness reduction support (transparently using methods from skhubness.reduction).
  For example, you can apply hubness-reduced kNN classification to large, high-dimensional data sets.
• skhubness.reduction provides hubness reduction methods. The classes in this package can be used to transform kNN graphs directly.
  For example, you can compute a mutual proximity kNN graph.

Find documentation at https://scikit-hubness.readthedocs.io/.
The package is available at https://pypi.org/project/scikit-hubness/ and can be installed with pip:
$ pip install scikit-hubness

All major platforms are supported.

Please have a look at the Changelog to see what's new compared to pre-releases.