Which of the following parameters can be tuned for finding good ensemble model in bagging based algorithms?
1. Max number of samples
2. Max features
3. Bootstrapping of samples
4. Bootstrapping of features

A. training based on historical data B. prediction to answer a query C. both A and B D. automization of complex tasks

A. scalable B. accuracy C. fast D. all of the above

A. machine learning model B. machine learning algorithm C. null D. accuracy

A. data mining. B. artificial intelligence C. big data computing D. internet of things