umap-learn

SKILL.md

UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique for visualization and general non-linear dimensionality reduction. Apply this skill for fast, scalable embeddings that preserve local and global structure, supervised learning, and clustering preprocessing.

UMAP follows scikit-learn conventions and can be used as a drop-in replacement for t-SNE or PCA.

Critical preprocessing requirement: Always standardize features to comparable scales before applying UMAP to ensure equal weighting across dimensions.

UMAP 降维。针对高维数据的 2D/3D 可视化、聚类预处理 (HDBSCAN)、监督/参数 UMAP 的快速非线性流形学习。 来源：ovachiever/droid-tings。

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