StatQuest: Random Forests Part 2: Missing data and clustering

NOTE: This StatQuest is the updated version of the original Random Forests Part 3 and includes two minor corrections.

Last time we talked about how to create, use and evaluate random forests. Now it's time to see how they can deal with missing data and how they can be used to cluster samples, even when the data comes from all kinds of crazy sources.

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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