AI engineering glossary · Feature engineering data prep
What is embedded method?
Embedded method: A feature selection approach in which selection happens during model training, as with L1 regularisation shrinking coefficients to zero or a tree ensemble ranking feature importance. It balances the speed of filters and the accuracy of wrappers.
Embedded method: an example
Training a lasso model zeroes out the coefficients of 60 of 100 features, leaving the 40 that matter.
Related terms
More Feature engineering data prep terms
- Entity embedding
- Equal-frequency binning
- Equal-width binning
- Feature crossing
- Feature engineering
- Feature extraction
- Feature scaling
- Feature selection
Where you learn it
Embedded method is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.