Machine Learning, Uc Berkeley, Random Forest, Decision Tree, Ensemble Learning.
noise in the data will be “predicted” and corrected, resulting in an ensemble that is very accurate on training data, but not as accurate on testing data. Bagging vs. Boosting Before we try applying novel forms of ensemble learning to decision tree, let’s understand the basic strategies that both