umap-learn 0.5.6
0
Uniform Manifold Approximation and Projection
Contents
Uniform Manifold Approximation and Projection
Stars: 7401, Watchers: 7401, Forks: 805, Open Issues: 477The lmcinnes/umap
repo was created 7 years ago and the last code push was Yesterday.
The project is extremely popular with a mindblowing 7401 github stars!
How to Install umap-learn
You can install umap-learn using pip
pip install umap-learn
or add it to a project with poetry
poetry add umap-learn
Package Details
- Author
- None
- License
- BSD
- Homepage
- http://github.com/lmcinnes/umap
- PyPi:
- https://pypi.org/project/umap-learn/
- GitHub Repo:
- https://github.com/lmcinnes/umap
Classifiers
- Scientific/Engineering
- Software Development
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Errors
A list of common umap-learn errors.
Code Examples
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code examples and snippets.
GitHub Issues
The umap-learn package has 477 open issues on GitHub
- [Feature Request] Allow support for "precomputed" distance matrix for umap.umap_.fuzzy_simplicial_set
- tighten test_umap_trustworthiness_fast_approx bound
- continuous UMAP latent space
- No module named 'umap'
- module 'umap' has no attribute 'UMAP'
- module 'umap' has no attribute 'version'
- Using the transform function and binary metrics for new data doesn't seem to work properly
- [Error] What if I want to apply embedding_column to category variables in Parametric UMAP?
- No conversion from array(float32, 2d, F) to array(float32, 2d, C) for 'knn_dists', defined at None
- Test failure in test_save_load with tensorflow 2.7: Unknown loss function: loss.
- Module Keras/tensorflow_probability not found when importing Parametric UMAP
- ParametricUMAP.save() compatability with Google Cloud Storage paths
- update function of UMAP does not work
- Support for wasserstein (earth mover's) distance
- LLVM ERROR: Symbol not found: __svml_sqrtf8