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UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
umap-learn is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # UMAP-Learn ## Overview UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique for visualization and general non-linear d. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding umap-learn to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
codex skill install jackychenlu/skill-demoReview the upstream source before running this command.
Scan coverage: Install metadata and the indexed document body.
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# UMAP-Learn ## Overview UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique for visualization and general non-linear dimensionality reduct