AI engineering glossary · Classical ML algorithms
What is boosting?
Boosting: An ensemble strategy that builds models one after another, each concentrating on the examples earlier models got wrong, then adds them up with weights. It steadily reduces bias and usually wins on structured tabular data, but is more sensitive to noise than bagging.
Boosting: an example
After tree 1 misclassifies 100 of 1,000 rows, tree 2 is trained with those rows emphasised.
Related terms
More Classical ML algorithms terms
Where you learn it
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.