Which statements are true regarding the weight of a tree in the AdaBoost algorithm? Question 14 options: Better classifiers are given exponentially more weight Weight is zero if the error rate is 0.5. At 0 (zero) accuracy (everything is misclassified), the model's decision is 100% trusted, and thus the weight is at its maximum A classifier with 50% accuracy is no better than random guessing, so there is no value in it