Random Forests Trend 2026

A powerful ensemble learning method, Random Forests combines multiple decision trees to improve prediction accuracy and control overfitting. It handles classification and regression tasks by averaging numerous trees, each trained on random data subsets. Data scientists, financial analysts, and healthcare researchers benefit from its robustness, using it for fraud detection, risk assessment, and medical diagnosis.