Random Forest, introduced in 2001 by Leo Breiman and Adele Cutler, combines multiple decision trees to enhance prediction accuracy and reduce overfitting. It is a versatile machine learning tool widely applied in healthcare, transport planning, and environmental risk assessment in Australia.
