2. Consider the training data shown in the following table. (1) Estimate the conditional probabilities for P(A+) (i.e., P(A=0 Class =+)= ? P(A=1 Class =+)=?), P(B+),P(C+),P(A),P(B),P(C).(24 points ) (2) Using Nave Bayesian classifier and the conditional probabilities estimated in (1), predict class labels for the two records: X1=(A=0,B=1,C=0),X2=(A=1, B=1,C=1). (20 points) Note: If P( Class =+X)=P( Class =X), we can regard its class label as 0 . This rule may or may not be useful for this exercise. Training Data for Exercise 2 \begin{tabular}{|c|c|c|c|c|} \hline Record ID & A & B & C & Class \\ \hline 1 & 0 & 0 & 0 & + \\ \hline 2 & 1 & 0 & 0 & - \\ \hline 3 & 1 & 0 & 1 & - \\ \hline 4 & 1 & 0 & 1 & - \\ \hline 5 & 1 & 0 & 0 & + \\ \hline 6 & 1 & 1 & 0 & + \\ \hline 7 & 1 & 1 & 0 & - \\ \hline 8 & 1 & 1 & 0 & - \\ \hline 9 & 1 & 1 & 1 & + \\ \hline 10 & 1 & 1 & 0 & + \\ \hline \end{tabular}