How does Random Forest differ from a single decision tree?
- Random Forest always performs worse
- Random Forest focuses on one feature
- Random Forest uses multiple trees and averages their predictions
- Random Forest uses only one tree
Random Forest is an ensemble method that builds multiple decision trees and averages their predictions. Unlike a single decision tree, it typically offers higher accuracy and robustness by reducing overfitting through the combination of multiple trees' predictions.
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