What is a Random Forest?

Random Forest is an ensemble learning method that builds multiple decision trees and combines their outputs for better accuracy and stability.

Random Forest works by training many decision trees on different random subsets of data and features. The final prediction is made by averaging (regression) or majority voting (classification). This reduces overfitting compared to a single decision tree.