A random forest is an ensemble learning method used for classification and regression. It operates by constructing multiple decision trees during training and outputting the mode of the classes (classification) or mean prediction (regression) of the individual trees. This method is known for its robustness and accuracy, making it a popular choice in various fields, including cancer research.
