Changelog

0.21.0 - 2019-11-25

This is the first major release of scikit-hubness.

Added

  • 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.

Changes

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

Fixes

  • 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

Added

  • General structure for docs

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

  • Enable Puffinn LSH also on MacOS

Fixes

  • Correct mutual proximity (empiric) calculation

  • Better handling of optional packages (ANN libraries)

Maintenance

  • streamlined CI builds

  • several minor code improvements

New contributors

  • Silvan David Peter

0.21.0a8 - 2019-09-12

Added

  • 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)

Fixes

  • 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