AI engineering glossary · Classical ML algorithms
What is GBM (gradient boosting)?
Gradient boosting (also called GBM, Gradient boosted trees): A boosting method that adds trees one at a time, each fitted to the errors (the negative gradient of the loss) of the current ensemble. A learning rate scales each tree's contribution. It is highly accurate on tabular data and underlies XGBoost, LightGBM and CatBoost.
Gradient boosting: an example
For house prices, tree 1 predicts 50 lakh where truth is 58; tree 2 learns the +8 residual and adds a fraction of it.
Related terms
More Classical ML algorithms terms
Where you learn it
Gradient boosting is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.