Tree Ensembles: Bagging, Random Forests and Boosting

This video introduces three popular machine-learning methods: bagging, random forests, and boosting. All three methods combine multiple simple models, usually regression or classification trees, to form an "ensemble" that achieves better performance than the individual models. We explain the guiding principles behind each method’s ensembling strategy and illustrate them using a real-world dataset. Probability and statistics book: https://a.co/d/7k259eb Website with free preprint, videos, slides and solutions to exercises: https://www.ps4ds.net Slides for this video: https://github.com/cfgranda/ps4ds/blo... Code: https://github.com/cfgranda/ps4ds/blo...