XGBoost Part 2 (of 4): Classification

In this video we pick up where we left off in part 1 and cover how XGBoost trees are built for Classification.

NOTE: This StatQuest assumes that you are already familiar with...

XGBoost Part 1: XGBoost Trees for Regression:    • XGBoost Part 1 (of 4): Regression  
...the main ideas behind Gradient Boost for Classification:    • Gradient Boost Part 3 (of 4): Classif...  
...Odds and Log(odds):    • Odds and Log(Odds), Clearly Explained!!!  
...and how the Logistic Function works:    • Logistic Regression Details Pt 2: Max...  

Also note, this StatQuest is based on the following sources:
The original XGBoost manuscript: https://arxiv.org/pdf/1603.02754.pdf
The original XGBoost presentation: https://homes.cs.washington.edu/~tqch...
And the XGBoost Documentation: https://xgboost.readthedocs.io/en/lat...

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Corrections:
14:24 I meant to say "larger" instead of "lower.
18:48 In the original XGBoost documents they use the epsilon symbol to refer to the learning rate, but in the actual implementation, this is controlled via the "eta" parameter. So, I guess to be consistent with the original documentation, I made the same mistake! :)

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