It’s 2030, and you are playing a massive multi-player game in the Metaverse.
Don’t ask how you got here. You don’t have time for these questions. You need to focus on staying alive.
A massive snake with three heads and bloody eyes comes charging after you. It’s not looking good!
You have enough breath to read a clue written on the walls at the last second: “bootstrap it, and you’ll live,” it says.
Where would you hide? Only one of these places will save your life:
Behind a tree
In the forest
In a cave
In a hole
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I hope this was a fun question.
As you would expect, the answer is in the clue written on the walls. “Bootstrap it, and you’ll live” doesn’t say much until you see the four hiding spots: A tree, a forest, a cave, and a hole.
Bootstrap aggregating, also called “bagging,” is a popular machine learning ensembling technique. We usually use bagging with decision trees, and one of the hiding spots is a tree, so that could be the answer! In reality, there’s an even better answer.
Random Forest is an algorithm that consists of many individual decision trees. It uses bootstrap aggregating to combine these trees to reach a solution much better than the one provided by any of the individual trees.
“Bootstrapping” is more closely related to Random Forest than Decision Trees, so you’ll stay alive if you hide in the forest.
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