Machine Learning

UMAP

A fast dimensionality-reduction method that preserves local and global structure.

UMAP constructs a graph describing how observations are connected in high-dimensional space and then creates a lower-dimensional representation with a similar structure.

It is commonly used to visualise embeddings and large datasets. UMAP is often faster than t-SNE and may preserve more global structure, although its output is still affected by parameter choices.

Also in Machine Learning

Supervised Learning Unsupervised Learning K-Means K-Nearest Neighbours Logistic Regression Linear Regression

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