tags: [AI/Tasks/Regression, AI/Algorithms/DecisionTrees ]
aliases: [Random Forest Regression, RFR]
Random Forest Regression (RFR) is an Ensemble Learning Method that utilizes multiple Decision Trees to make predictions. Each tree in the Random Forest is built independently, and the final prediction is determined by averaging the predictions of all the individual trees. Through random sampling of the training data and features, along with the creation of a multitude of trees, RFR provides improved predictive accuracy and greater resistance to Overfitting compared to a single decision tree regression model.
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