lmcinnes/umap
UMAP is a Python library implementing the Uniform Manifold Approximation and Projection algorithm for dimensionality reduction and visualization.
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UMAP provides a general-purpose dimensionality reduction technique based on assumptions of uniform distribution on Riemannian manifolds. It offers competitive performance compared to t-SNE while preserving both local and global structure. The library integrates with scikit-learn and supports applications including visualization, clustering pre-processing, and general non-linear dimension reduction.
Frequently asked
- What is lmcinnes/umap?
- UMAP is a Python library implementing the Uniform Manifold Approximation and Projection algorithm for dimensionality reduction and visualization.
- Is umap open source?
- Yes — lmcinnes/umap is open source, released under the BSD-3-Clause license.
- What language is umap written in?
- lmcinnes/umap is primarily written in Python.
- How popular is umap?
- lmcinnes/umap has 8.2k stars on GitHub.
- Where can I find umap?
- lmcinnes/umap is on GitHub at https://github.com/lmcinnes/umap.