Random Forest Algorithm Trend 2026

A random forest algorithm combines multiple decision trees to improve predictive accuracy and control overfitting. It handles classification and regression tasks by averaging outcomes from many trees. Data scientists, financial analysts, and healthcare researchers benefit from its robustness in fraud detection, stock forecasting, and medical diagnosis.