Random Forest is an ensemble method that consists of a multitude of decision trees and uses a technique known as __________ to create diversity among them.

  • Bagging
  • Boosting
  • Bootstrapping
  • nan
Random Forest uses bagging (bootstrap aggregating) to create diversity among its constituent decision trees by training each tree on a different random subset of the data.
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