In the following video, Snehanshu will give you a walkthrough on the notebook on how to implement the AdaBoost algorithm in python. In this exercise, you have to go through the notebook attached to the page and answer the questions that follow.
So, now that you have gone through the video, download and implement the code in the above notebook by yourself to get an understanding of the AdaBoostClassifier and to answer the following questions.
Refer to the documentation of AdaBoostClassifier if needed.
You can try changing the number of trees in ‘estimators = list(range(1, 50, 3))’ to ‘estimators = list(range(1, 200, 3))’ and see if the acuracy increases.
Note that we have used ‘accuracy_score’ as the evaluation metric here. We can use other evaluation metrics also like ‘roc_auc_curve’.