StatQuest: Random Forests Part 1 - Building, Using and Evaluating

Random Forests make a simple, yet effective, machine learning method. They are made out of decision trees, but don't have the same problems with accuracy. In this video, I walk you through the steps to build, use and evaluate a random forest.

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NOTE: Random Forests are made from Decision Trees, so if you don't know about those, here's the Quest: https://youtu.be/7VeUPuFGJHk

ALSO NOTE: This StatQuest is based on Leo Breiman's (one of the creators of Random Forests) website: https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm

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0:00 Awesome song and introduction
0:31 Motivation for using Random Forests
1:17 Step 1, create a bootstrapped dataset
2:23 Step 2, create a decision tree a random subset of variables at each step
4:00 Step 3, repeat steps 1 and 2 a bunch of times
4:40 Classifying a new sample with a Random Forest
5:41 Definition of Bagging
6:03 Evaluating a Random Forest
8:34 Optimizing the Random Forest
#statquest #randomforest #ML

Видео StatQuest: Random Forests Part 1 - Building, Using and Evaluating канала StatQuest with Josh Starmer