Tree-Based Models in R

Classification Trees
-This chapter covers supervised machine learning with classification trees.

Regression Trees
-In this chapter you'll learn how to use a single tree for regression, instead of classification.

agged Trees
-In this chapter, you will learn about Bagged Trees, an ensemble method, that uses a combination of trees (instead of only one).

Random Forests
-In this chapter, you will learn about the Random Forest algorithm, another tree-based ensemble method. Random Forest is a modified version of bagged trees with better performance. Here you'll learn how to train, tune and evaluate Random Forest models in R.

oosted Trees
-In this chapter, you will see the boosting methodology with a focus on the Gradient Boosting Machine (GBM) algorithm, another popular tree-based ensemble method. Here you'll learn how to train, tune and evaluate GBM models in R.