Question: Why is it common in data science to break an original data set into a training data set and a testing data set? Select an

Why is it common in data science to break an original data set into a training data set and a testing data set?
Select an answer:
to control for loss of data in the original data set
to control for tendencies toward the role of chance
to control for unexpected market situations
to control for tendencies toward false positives

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