lmcinnes

license

BSD-3-Clause(OSI)

source

public(github.com/lmcinnes/umap)

core features withheld

no — maintained by its author

BSD-3-Clause and built from the public repository, which its author maintains. There is no company, paid tier or commercial edition behind it.

• https://raw.githubusercontent.com/lmcinnes/umap/master/LICENSE.txt recorded 2026-09-27

  LICENSE.txt is the "BSD 3-Clause License", "Copyright (c) 2017, Leland McInnes".

• https://raw.githubusercontent.com/lmcinnes/umap/master/README.rst recorded 2026-09-27

  README closes "If you still have questions then please open an issue and I will try to provide any help and guidance that I can."; no paid tier, hosted service or commercial license mentioned.

• https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmcinnes/umap recorded 2026-09-27

  Repository record for lmcinnes/umap, not archived and not a fork, license bsd-3-clause, last pushed 2026-09-24.

• https://ungh.cc/repos/lmcinnes/umap/files/master recorded 2026-09-27

  Repository tree of 319 paths with no ee, enterprise, commercial or pro directory.

Measured on monthly PyPI downloads of umap-learn, the package name the project publishes under.

• https://pypistats.org/api/packages/umap-learn/recent recorded 2026-09-27

  last_month 5,332,757 downloads of umap-learn

UMAP does one thing, embedding data in fewer dimensions, and its variants all build on that method. It is usually one step in a pipeline assembled with other tools, such as HDBSCAN for clustering the embedding.

• https://raw.githubusercontent.com/lmcinnes/umap/master/README.rst recorded 2026-09-27

  README: "Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction."; "UMAP supports supervised and semi-supervised dimension reduction"; "Parametric UMAP provides support for training a neural network to learn a UMAP based transformation of data."

• https://umap-learn.readthedocs.io/en/latest/api.html recorded 2026-09-27

  API reference documents the umap.umap_.UMAP estimator with fit, fit_transform, transform and inverse_transform.