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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