Chapter 8 Tree-based methods

Learning objectives:

• Use basic decision trees to model relationships between predictors and an outcome

• Compare and contrast tree-based models with other model types

• Use tree-based ensemble methods to build (better!) predictive models

• Compare and contrast the various methods of building tree ensembles: bagging, boosting, random forests, and Bayesian Additive Regression Trees (BART)

• Source: material for this chapter was adapted from https://github.com/JauntyJJS/islr2-bookclub-cohort3-chapter8, https://hastie.su.domains/ISLR2/Slides/Ch8_Tree_Based_Methods.pdf