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Go Classes | DA Course | Machine Learning

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Sara can't believe everyone she knows only decided to watch one of Barbie or Oppenheimer. She collects data and gives each person a label of $y_i=1$ if a person watched Barbie, and $y_i=0$ if a person watched Oppenheimer. Assume that everybody in the dataset only watched one of the movies. Suppose Sara believes that wrongly predicting Barbie is worse than wrongly predicting Oppenheimer.

Which quantity should she aim to minimize?

 A. True Positives

B. False Positives

C. True Negatives

D. False Negatives

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Solution: We never want to minimize true positives or true negatives. Wrongly predicting a value of 1 is worse than wrongly predicting a value of 0 . This means a false positive is worse than a false negative.
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