AI engineering glossary · Classical ML algorithms
What is dimensionality reduction?
Dimensionality reduction: Transforming data with many features into a smaller set of features while keeping as much useful structure as possible. It speeds up learning, removes noise, reduces storage and makes it possible to draw 2-D or 3-D plots of the data.
Dimensionality reduction: an example
Compressing 1,000 gene-expression columns into 20 derived columns.
Related terms
More Classical ML algorithms terms
- Elastic net
- Elbow method
- Ensemble learning
- Entropy
- Euclidean distance
- Expectation-maximisation
- Explained variance ratio
- Extremely randomised trees
Where you learn it
Dimensionality reduction is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.