Decision and Classification Trees, Clearly Explained!!!

Decision trees are part of the foundation for Machine Learning. Although they are quite simple, they are very flexible and pop up in a very wide variety of situations. This StatQuest covers all the basics and shows you how to create a new tree from scratch, one step at a time.

NOTE: This is an updated and revised version of the Decision Tree StatQuest that I made back in 2018. It is my hope that this new version does a better job answering some of the most frequently asked questions people asked about the old one.

Note, you may also want to learn about...
Regression Trees:    • Regression Trees, Clearly Explained!!!  
Bias and Variance (and over fitting):    • Machine Learning Fundamentals: Bias and Va...  
Cross Validation:    • Machine Learning Fundamentals: Cross Valid...  
Pruning Trees:    • How to Prune Regression Trees, Clearly Exp...  

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0:00 Awesome song and introduction
0:18 Basic decision tree concepts
3:16 Building a tree with Gini Impurity
9:15 Numeric and continuous variables
12:35 Adding branches
13:56 Adding leaves
14:32 Defining output values
15:12 Using the tree
15:38 How to prevent overfitting

#StatQuest #decisiontree #ML