0.21.1 - 2019-12-10

This is a bugfix release due to the recent update of scikit-learn to v0.22.


  • Require scikit-learn v0.21.3.

    Until the necessary adaptions for v0.22 are completed, scikit-hubness will require scikit-learn v0.21.3.

0.21.0 - 2019-11-25

This is the first major release of scikit-hubness.


  • Enable ONNG provided by NGT (optimized ANNG). Pass optimize=True to NNG.

  • User Guide: Description of all subpackages and common usage scenarios.

  • Examples: Various usage examples

  • Several tests

  • Classes inheriting from SupervisedIntegerMixin can be fit with an ApproximateNearestNeighbor or NearestNeighbors instance, thus reuse precomputed indices.


  • Use argument algorithm='nng' for ANNG/ONNG provided by NGT instead of 'onng'. Also set optimize=True in order to use ONNG.


  • DisSimLocal would previously fail when invoked as hubness='dis_sim_local'.

  • Hubness reduction would previously ignore verbose arguments under certain circumstances.

  • HNSW would previously ignore n_jobs on index creation.

  • Fix installation instructions for puffinn.

0.21.0a9 - 2019-10-30


  • General structure for docs

  • Enable NGT OpenMP support on MacOS (in addition to Linux)

  • Enable Puffinn LSH also on MacOS


  • Correct mutual proximity (empiric) calculation

  • Better handling of optional packages (ANN libraries)


  • streamlined CI builds

  • several minor code improvements

New contributors

  • Silvan David Peter

0.21.0a8 - 2019-09-12


  • Approximate nearest neighbor search

    • LSH by an additional provider, puffinn (Linux only, atm)

    • ANNG provided by ngtpy (Linux, MacOS)

    • Random projection forests provided by annoy (Linux, MacOS, Windows)


  • Several minor issues

  • Several documentations issues

0.21.0a7 - 2019-07-17

The first alpha release of scikit-hubness to appear in this changelog. It already contains the following features:

  • Hubness estimation (exact or approximate)

  • Hubness reduction (exact or approximate)

    • Mutual proximity

    • Local scaling

    • DisSim Local

  • Approximate nearest neighbor search