Random forests or random decision forests are an
ensemble learning method for
classification,
regression and other tasks, that operate by constructing a multitude of
decision trees at training time and outputting the class that is the
mode of the classes (classification) or mean prediction (regression) of the individual trees. Random decision forests correct for decision trees' habit of
overfitting to their
training set