. . . . . . . . can be adopted when it's necessary to categorize a large amount of data with a few complete examples or when there's the need to impose some constraints to a clustering algorithm.

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