In AdaBoost, what happens during each iteration of training? a$)$ A weak learner is trained on the entire dataset. b$)$ A weak learner is trained on the misclassified data points from the previous iteration. c$)$ A weak learner is trained on a subset of the dataset. d$)$ A strong learner is trained on the misclassified data points from the previous iteration.