AI engineering glossary · Classical ML algorithms
What is lasso regression?
Lasso regression (also called L1-regularised regression): A least-squares variant that adds a penalty equal to the sum of absolute weight values. Because of the sharp corner of that penalty, some weights become exactly zero, so the model both fits and selects features. It suits datasets with many features where only a few matter.
Lasso regression: an example
With 200 candidate features and Lasso(alpha=0.1), perhaps only 12 keep non-zero weights, giving a compact model that is easy to explain.
Related terms
More Classical ML algorithms terms
- Lazy learning
- Lift
- LightGBM
- Linear discriminant analysis
- Linear regression
- Linkage criterion
- Local outlier factor
- Log-odds
Where you learn it
Lasso regression is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.