Dimensionality reduction

Dimensionality reduction is a set of techniques that compress data with many features into fewer features while preserving its important structure, making it easier to visualize, store, or model.

Dimensionality reduction sits in the Foundations part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.

Also called PCA, t-SNE, UMAP.