Machine Learning, Uc Berkeley, Random Forest, Decision Tree, Ensemble Learning.
bagging, we throw our training data into a proverbial “bag” and repeatedly sample (take individual data points) from that bag, putting the data back into the bag every time. Then we use those data points to train our classifier. This is called sampling with replacement, or bootstrapping. By