What is Boosting?

What is Boosting?

Approach: Describe the sequential improvement of weak learners.

An ensemble technique that attempts to create a strong classifier from a number of weak classifiers. It does this by building a model from the training data, then creating a second model that attempts to correct the errors from the first model.

Follow-up: How does it differ from Bagging?

Key concepts: adaboost, gradient boosting, weak learners.