What are Random Forests?
Random forests are an ensemble learning method for classification and regression that build numerous decision trees at training time. For classification tasks, the output of the random forest is the mode of the classes (classification) or the mean prediction (regression) of the individual trees.
They are popular due to their accuracy and robustness compared to other classifiers, and their ability to handle a large number of features.