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?

c

step-by-step explanation:

at least i think its

81 seats

step-by-step explanation:

if you multiply 0.65 times 125 then you get 81.5 seats. well since you can't have half of a seat you have to round down and get 81 seats in the no children zones. that leave 44 seats outside of the no children zone.

.24

step-by-step explanation:

the probability is   .24

the first player had the highest probability of getting a silver marble

the game could be made fair by adding back the marble that was drawn after each draw

step by step solution :

step   1   :

1.1     4 = 22

(4)3 = (22)3 = 26

equation at the end of step   1   :

  ((23) • 26)2

step   2   :

equation at the end of step   2   :

  (23 • 26)2

step   3   :

final result :

  218

ya