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 降維。針對高維數據的 2D/3D 可視化、聚類預處理 (HDBSCAN)、監督/參數 UMAP 的快速非線性流形學習。 來源：ovachiever/droid-tings。

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