1. Consider each of the following machine learning problems. Would the problem be best approached as a classification problem or a regression problem? Provide a rationale for your answer.

a. Predicting the number of fish caught on a commercial fishing voyage

b. Identifying likely adopters of a new technology

c. Using weather and population data to predict bicycle rental rates

d. Predicting the best marketing campaign to send a specific person 2. You developed a machine learning algorithm that assesses a patient’s risk of heart attack (a positive event) based on a number of diagnostic criteria. How would you describe each of the following events?

a. Your model identifies a patient as likely to suffer a heart attack, and the patient does suffer a heart attack.

b. Your model identifies a patient as likely to suffer a heart attack, and the patient does not suffer a heart attack.

c. Your model identifies a patient as not likely to suffer a heart attack, and the patient does not suffer a heart attack.

d. Your model identifies a patient as not likely to suffer a heart attack, and the patient does suffer a heart attack.