Classification Interpretation You have built a model to identify patients at risk of heart attacks. Your target classes are: At risk (Postive, 1) Not At risk (Negative, 0) Considering the scenario and looking at the confusion matrix below, which of the following are true?

a) The accuracy of this model is 0.69.

b) We should be concerned about the number of false negatives.

c) Our model clearly does a good job, since it reduces the number of false positives.

d) Our model should, in general, be adjusted to make less positive predictions.