Machine Learning, Uc Berkeley, Random Forest, Decision Tree, Ensemble Learning.
classifiers won’t be useful if they are all identical. So we must train them in ways so that they each specialize in some aspect of the problem. Two examples of this are bagging and boosting, which are covered in the next section. Bagging and Boosting Bagging (aka Bootstrap Aggregation): In