Regression Trees are one of the fundamental machine learning techniques that more complicated methods, like Gradient Boost, are based on. They are useful for times when there isn't an obviously linear relationship between what you want to predict, and the things you are using to make the predictions. This StatQuest walks you through the steps required to build Regression Trees so that they are Clearly Explained.

NOTE: This StatQuest assumes you already know about...
The bias/variance tradeoff: [ Ссылка ]
Decision Trees: [ Ссылка ]
Linear Regression: [ Ссылка ]

ALSO NOTE: This StatQuest is based on the definition of Regression Trees found on page 328 to 331 of the Introduction to Statistical Learning. [ Ссылка ]

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0:00 Awesome song and introduction
0:41 Motivation for Regression Trees
2:19 Regression Trees vs Classification Trees
7:11 Building a Regression Tree with one variable
18:59 Building a Regression Tree with multiple variables
20:54 Summary of concepts and main ideas


#statquest #regression #tree

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