Random Forest

Random Forest is an ensemble learning method for classification, regression, and other tasks that operates by constructing a multitude of decision trees at training time. It outputs the mode of the classes (classification) or mean prediction (regression) of the individual trees.

Random Forest in Practice

Random Forests are known for their high accuracy, robustness, and ease of use. They handle both categorical and continuous data and provide a measure of feature importance. They are less likely to overfit than a single decision tree.