_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
python-umap-learn 0.5.6
Propagated dependencies: python-numba@0.59.1 python-numpy@1.24.4 python-pynndescent@0.5.11 python-scikit-learn@1.4.2 python-scipy@1.12.0 python-tqdm@4.67.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/lmcinnes/umap
Licenses: Modified BSD
Synopsis: Uniform Manifold Approximation and Projection
Description:

Uniform Manifold Approximation and Projection is a dimension reduction technique that can be used for visualization similarly to t-SNE, but also for general non-linear dimension reduction.

Total results: 1