Release Notes¶
Some notes on new features in various releases
What’s new in 0.5¶
- ParametricUMAP learns embeddings with neural networks.
- AlignedUMAP can align multiple embeddings using relations between datasets.
- DensMAP can preserve local density information in embeddings.
- UMAP now depends on PyNNDescent, but has faster more parallel performance as a result.
- UMAP now supports an
update
method to add new data and retrain. - Various performance improvements and bug fixes.
- Additional plotting support, including text searching in interactive plots.
- Support for “maximal distances” in neighbor graphs.
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.