Bagging Quiz (Easy)

What does the term “Bagging” stand for in machine learning?

What is the primary purpose of Bagging? 

In Bagging, how is the training dataset for each model created? 

Which of the following is an example of a Bagging algorithm? 

How does Bagging help in reducing variance?

What is the key difference between Bagging and Boosting?

In Bagging, what method is commonly used to aggregate predictions?

What is the primary idea behind the “ensemble” nature of bagging? 

Which algorithm is commonly used as a base learner in bagging? 

What is the purpose of the “max_samples” hyperparameter in the Scikit-Learn BaggingClassifier?

In Bagging, how does increasing the number of base learners impact training time and prediction time, respectively? 

In the context of decision tree ensembles, what is “bagging”?