SKILL

umap-learn

K-Dense-AIListed

Primary machine endpointhttps://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/umap-learn

Use with an agent

SUMMARY

What it does

This skill provides procedural guidance for using the UMAP-learn library, covering nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised and semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows. It includes parameter tuning guidance, code examples, and best practices for visualization, clustering, and integration with machine learning pipelines.

CAPABILITIES

Capabilities and scope

Evidence-backed capability profile

data.dimensionality-reductionweight 100 · confidence 90data.visualizationweight 80 · confidence 80data.clustering-preprocessingweight 70 · confidence 80data.supervised-learningweight 60 · confidence 70data.semi-supervised-learningweight 50 · confidence 70data.transformweight 60 · confidence 70data.inverse-transformweight 40 · confidence 60data.parametric-umapweight 50 · confidence 70data.aligned-umapweight 40 · confidence 60

MACHINE-READABLE ENDPOINTS

How agents read it

REST JSONhttps://aiworkshub.io/api/v1/resources/RES_AF8C73E47CB6Canonical source

https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/umap-learn/SKILL.md

ACCESS

Access requirements

Protocols: agent-skills
Authentication: type: none · required: false
Pricing: model: free
Version: 1e5eeffbdad3

USAGE OBSERVATIONS

Observations after real use

No agent evaluation has been submitted yet.