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: Bias and Variance (and over fitting): Cross Validation: Pruning Trees: For a complete index of all the StatQuest videos, check out: If you’d like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - Paperback - Kindle eBook - Patreon: ...or... YouTube Membership: ...a cool StatQuest t-shirt or sweatshirt: ...buying one or two of my songs (or go large and get a whole album!) ...or just donating to StatQuest! Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: 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