Problem $2$A $-$ Naive Bayesian classifier. $[30$pts$]$; $\{\frac{2}{3}\}$ Given the training dataset in table $1$ below $($Buy Computer data$),$ predict the class of the following new record using Nave Bayes classification:

$\{$ age $30,$ income $=$ medium, student $=$ yes, credit rating $=$ fair $\}$

$\backslash$table$[[$RID$,$age,income,seudent,credit$\_$rating,Class: buys$\_$computer$],[1,30,$high,no$,$fair,no$],[2,30,$high,no$,$excellent,no$],[3,31$dots$40,$high,no$,$fair,yes$],[4,>40,$medium,no$,$fair,yes$],[5,>40,$low,yes,fair,yes$],[6,>40,$low,yes,excellent,no$],[7,31$dots.dots$0,$low,yes,excellent,yes$],[8,30,$medium,no$,$fair,no$],[9,30,$low,yes,fair,yes$],[10,>40,$medium,yes,fair,yes$],[11,30,$medium,yes,excellent,yes$],[12,31$dots$40,$medium,no$,$excellent,yes$],[13,31$dots$40,$high,yes,fair,yes$],[14,>10,$medium,no$,$excellent,no$]]$

Table $1$: Naive Bayes training data for Problem $5.$G

Show computation of the following:

$2$pt: For computation of each absolute probability $($per each$)$

$4$pts: For computation of each necessary conditional probability of attributes $($per each$)$

$2$pts: for computation of each Bayes decision value necessary $($per cach$)$