1. Consider the data set shown in Table below: Instance A B C Class 1 0 0 0 + 2 0 0 1 - 3 0 1 1 - 4 0 1 1 - 5 0 0 1 + 6 1 0 1 + 7 1 0 1 - 8 1 0 1 - 9 1 1 1 + 10 1 0 1 + (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 naive Bayes approach. (c) Estimate the conditional probabilities using the m-estimate approach, with p: I/2 and m:4. (d) Repeat part (b) using the conditional probabilities given in part (c). (e) Compare the two methods for estimating probabilities. Which method is better and why?