Glossary · Phase 3 · Machine learning
Dimensionality reduction
Squeezing many columns into a few while keeping most of the information, to speed models up or to draw data in 2D.
Learn it properly
Dimensionality reduction · Visualize and compress high-dimensional data. About 30 minutes.
Other terms from the same lesson
- explained variance ratio: The share of the data's spread that each PCA component keeps. Adding them up shows how much a few components hold.
- t-SNE: A way to draw high-dimensional data in 2D that keeps near neighbors together. Good for pictures, not as model input.
- UMAP: A faster cousin of t-SNE for drawing high-dimensional data, such as embeddings, in 2D.