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A pure Julia implementation of the Uniform Manifold Approximation and Projection dimension reduction algorithm. The umap function takes two arguments, X (a column-major matrix of shape (n_features, n_samples)), n_components (the number of dimensions in the output embedding), and various keyword arguments.
Features
- Use precomputed distances
- Fit a UMAP model to a dataset and transforming new data
- Examples available
- Documentation available
- Uniform Manifold Approximation and Projection dimension reduction algorithm
- Construct a model to use for embedding new data
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Categories
Data VisualizationLicense
MIT LicenseFollow UMAP.jl
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