Question
An online retailer uses a machine learning algorithm to predict whether an order will be returned or not. For online orders that are eventually returned,
An online retailer uses a machine learning algorithm to predict whether an order will be returned or
not. For online orders that are eventually returned, the algorithm predicts a return 90% of the time.
However, for orders that are not returned, the algorithm erroneously predicts a return 15% of the
time. Approximately 20% of orders received by the retailer are returned.
a. For a random order, what is the probability that the algorithm predicts it will be returned? **is this set up as a conditional or joint probability?
b. What is the probability that a random order is not returned and will be predicted as not
returned?
c. Suppose an order is predicted to be returned. What is the probability that it is actually returned?
d. For a random order, what is the probability that the algorithm makes a correct prediction (i.e.,
the order is returned and the algorithm predicts it is returned, or the order is not returned and
the algorithm predicts it is not returned)?
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