$($a$)$ Explain all dependencies in the given Bayesian network $($as shown below$)$ consisting

of three variables $x_1,x_2,x_3$ and the class attribute $Y.$

$(6$ marks$)$

Training dataset

Bavesian network

Testing dataset

$($b$)$ Create conditional probability tables $($CPTs$)$ for individual variables based on the

given training dataset $($as shown above$).$

$(8$ marks$)$

$($c$)$ Use the Bayesian rule and the created CPTs in Q$5.$b to predict the class label of the

given testing instance $($as shown above in the testing dataset$).$ You need to provide

step$-$by$-$step solutions.

Please solve ASAP