AdaBoost — Adaptive Boosting

Fact

An ensemble method with repeated reweighting of misclassified examples.

In Plain Words

AdaBoost is like a coach at free-throw practice. Miss the shot, and the next ball comes straight back to you.

It trains simple models again and again, so past misses get extra weight. It often sorts things into classes, but noisy data can make it chase junk.

Related Concepts

• Ensemble Learning
• Decision Tree
• Gradient Boosting
• Classification Task

Ensemble
AdaBoost combines many weak learners into one stronger predictor.

Decision Tree
AdaBoost often trains shallow Decision Trees as weak learners.

Gradient Boosting
Gradient Boosting follows the same idea of fixing mistakes round by round.

Classification
AdaBoost is often used to put examples into the right class.