Which of the following is / are true about weak learners used in ensemble model?
1. They have low variance and they don't usually overfit
2. They have high bias, so they can not solve hard learning problems
3. They have high variance and they don't usually overfit

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