Imbalanced Classifiers
1.Begin by writing the formula for each calculation, then show your steps to arrive at your answer.
a. Calculate Accuracy
b.Precision

c.Recall
d.F- Measure

2.Begin by writing the formula for each calculation, then show your steps to arrive at your answer.
a. Calculate Accuracy
b.Precision

c.Recall
d.F- Measure

Bayes Theorem
3. (a) Suppose the fraction of undergraduate students who smoke is 15% and
the fraction of graduate students who smoke is 23%. If one-fifth of the college students are graduate students and the rest are undergraduates, what is the probability that a student who smokes is a graduate student?
Answer
(b) Given the information in part (a), is a randomly chosen college student
more likely to be a graduate or undergraduate student?
Answer
(c) Repeat part (b) assuming that the student is a smoker.
Answer:
(d) Suppose 30% of the graduate students live in a dorm but only 10% of
the undergraduate students live in a dorm. If a student smokes and lives in the dorm, is he or she more likely to be a graduate or undergraduate student? You can assume independence between students who live in a dorm and those who smoke.
Answer:

Bayes Theorem
4.Consider the data set below.
a) Estimate the conditional probabilities for (P(A|+), P(B|+), P(C|+), P(A|-). P(B|-), P(C|-)
(b) Use the estimate of conditional probabilities given in the previous question to predict the class label for a test sample (A =0, B =1, C =0) using the naïve Bayes approach.