Demystifying Maths of Gradient Boosting – Towards Data Science

Boosting is an ensemble learning technique. Conceptually, these techniques involve: 1. learning base learners; 2. using all of the models to come to a final prediction. Ensemble learning techniques are of different types and all differ from each other in terms of how they go about implementing the learning process for the base learners and then using their output to give out the final result. Techniques that are used in ensemble learning are Bootstrap Aggregation (a.k.a. In this article, we shall discuss briefly about Bagging and then move on to Gradient Boosting which is the focus of this article.