AI engineering glossary · Classical ML algorithms
What is GMM (gaussian mixture model)?
Gaussian mixture model (also called GMM): A probabilistic model that assumes data come from a blend of several bell-shaped (normal) distributions, each with its own mean and spread. It gives soft cluster membership as probabilities and handles elliptical clusters, and is usually fitted with expectation-maximisation.
Gaussian mixture model: an example
A customer may belong 70% to the 'high spender' cluster and 30% to 'occasional'.
Related terms
- Expectation-maximisation
- K-means
- Normal distribution
- Soft clustering
More Classical ML algorithms terms
- Gaussian naive Bayes
- Gaussian process
- Gini impurity
- Gradient boosting
- HDBSCAN
- Hierarchical clustering
- Hinge loss
- ID3
Where you learn it
Gaussian mixture model is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.