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ivis: dimensionality reduction in very large datasets using Siamese Networks

Ignat Drozdov; Benjamin Szubert

Major features:

  • Support for semi-supervised dimensionality reduction
  • Switch from using fit_generator to fit for training the Keras model
  • Address eager execution issues with TF 2.0
  • User-configurable on-disk-building of Annoy index.
  • Tidy handling of interrupted multi-thread processes

Minor features:

  • Tests for semi-supervised DR
  • Improved input validation
  • Better hyper parameter validation
  • Slight changes to default hyperparameters

  • Bug fixes

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