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: https://youtu.be/g9c66TUylZ4
Bias and Variance (and over fitting): https://youtu.be/EuBBz3bI-aA
Cross Validation: https://youtu.be/fSytzGwwBVw
Pruning Trees: https://youtu.be/D0efHEJsfHo

⭐ NOTE: When I code, I use Kite, a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I love it! https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=statquest&utm_content=description-only

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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

Видео Decision and Classification Trees, Clearly Explained!!! канала StatQuest with Josh Starmer