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?