Release Notes

Some notes on new features in various releases

What’s new in 0.4

  • Inverse transform method. Generate points in the original space corresponding to points in embedded space. (Thanks to Joseph Courtney)
  • Different embedding spaces. Support for embedding to a variety of different spaces other than Euclidean. (Thanks to Joseph Courtney)
  • New metrics, including Hellinger distance for sparse count data.
  • New discrete/label metrics, including hierarchical categories, counts, ordinal data, and string edit distance.
  • Support for parallelism in neighbor search and layout optimization. (Thanks to Tom White)
  • Support for alternative methods to handling duplicated data samples. (Thanks to John Healy)
  • New plotting methods for fast and easy plots.
  • Initial support for dataframe embedding – still experimental, but worth trying.
  • Support for transform methods with sparse data.
  • Multithreading support when no random seed is set.

What’s new in 0.3

  • Supervised and semi-supervised dimension reduction. Support for using labels or partial labels for dimension reduction.
  • Transform method. Support for adding new unseen points to an existing embedding.
  • Performance improvements.

What’s new in 0.2

  • A new layout algorithm that handles large datasets (more) correctly.
  • Performance improvements.