Machine Learning, Data Science, Supervised Learning, Editors Pick, Getting Started.
each weak learner focuses on the hardest observations[1]. Boosting algorithms attribute more weight to the observations it misclassified. (Image by author) When you combine different weak learners sequentially, each one will make some incorrect predictions. But they will cover each others