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UMAP-Learn
Overview
UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction algorithm for visualization and general non-linear dimensionality reduction. It is faster than t-SNE, scales to larger datasets, preserves both local and global structure, and supports supervised learning and embedding of new data points.
When to Use
Reducing high-dimensional data to 2D/3D for visualization
Preprocessing for density-based clustering (HDBSCAN, DBSCAN)
Feature e
[Description truncada. Veja o README completo no GitHub.]
