🌳Random Forest is a powerful algorithm that uses multiple decision trees to make predictions.
🔄Random Forest addresses the issue of high variance in decision trees through bootstrapping and random feature selection.
🔢Random Forest combines the predictions of multiple decision trees using aggregation techniques like majority voting.
🧪Random Forest is less sensitive to training data and reduces correlation between trees, improving model performance.
📊Random Forest can be used for both classification and regression problems, providing accurate predictions in a variety of scenarios.