Machine Learning, Uc Berkeley, Random Forest, Decision Tree, Ensemble Learning.
final, overall prediction in the final ensemble model. On the other hand, in boosting, we iteratively train a decision tree on the error of previous decision trees, slowly generating our final ensemble model which is a linear combination and summation of our individual decision tree models.