alterlab-umap
CommunityVisualize high-D data with fast UMAP embeddings.
Data & Analytics#visualization#clustering#dimensionality-reduction#umap#hdbscan#parametric-umap#densmap
AuthorAlterLab-IEU
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Reducing complex, high-dimensional datasets to meaningful, low-dimensional representations for visualization, exploration, and downstream modeling.
Core Features & Use Cases
- Dimensionality reduction: obtain 2D/3D embeddings for visualization and exploratory analysis.
- Clustering preprocessing: enhance density-based clustering with informative embeddings (e.g., HDBSCAN).
- Advanced variants: supports Parametric UMAP, DensMAP, and AlignedUMAP for specialized workflows.
- Integration with ML pipelines: fits into sklearn pipelines and supports transform/inverse_transform workflows.
Quick Start
Run a basic embedding by fitting UMAP to your standardized features and visualize the 2D projection.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: alterlab-umap Download link: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/archive/main.zip#alterlab-umap Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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