| name | umap-learn |
| description | UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data. |
| source_skill_id | k-dense-ai-scientific-agent-skills-scientific-skills-umap-learn-skill-md |
| category | Science, research & data analysis |
| source_mirror | ../../../../../skills/by-category/science-research-data-analysis/latest-release-community/umap-learn/SKILL.md |
| benchmark_status | artifact_gated |
umap-learn
Use this skill when the task matches the description above or the source path clearly applies. Start with this concise entrypoint; open ../../../../../skills/by-category/science-research-data-analysis/latest-release-community/umap-learn/SKILL.md only when implementation details, commands, assets, or references are needed.
Workflow
- Confirm the task matches this skill's scope.
- Read the local source mirror if more detail is required.
- Follow repository-level
AGENTS.md; use one AI session only.
- Keep claims tied to files, commands, citations, or benchmark artifacts.
Verification
- Source mirror:
../../../../../skills/by-category/science-research-data-analysis/latest-release-community/umap-learn/SKILL.md
- Source commit:
eb20fb0dcb0b1dadaa3db2737188f0755bbc4770
- Static benchmark results: see
docs/benchmark-results.md
- Runtime artifacts recorded by this entrypoint:
0
- Assigned scenarios:
skill-proof-k-dense-ai-scientific-agent-skills-scientific-skills-umap-learn-skill-md, science-research-and-data-analysis-cellxgene-census, science-research-and-data-analysis-chembl, science-research-and-data-analysis-ome-ngff-samples
Do not claim this skill passed a runtime benchmark until a validated artifact exists.
