Machine Learning, Uc Berkeley, Random Forest, Decision Tree, Ensemble Learning.
and increased error on unfamiliar data. In practice, however, we can use pruning algorithms to reduce the depth and complexity of the tree by removing nodes (i.e. questions) larger than a certain depth so that the decision tree does not overfit to the training data. Decision Trees Classification