For Analytic Solver, partition data sets into $60\%$ training and $40\%$ validation and use $12345$ as the default random seed. If the predictor variable values are in the character format, then treat the predictor variable as a categorical variable. Otherwise, treat the predictor variable as a numerical variable. The accompanying data set contains two predictor variables $($x$\_1,$ x$\_2)$ and the target variable $($y$).$ Partition the data to develop a naive Bayes classification model where $\text{'}$ Y $\text{'}$ denotes the positive or success class for y$.$ Zelatureclick here for the Excel Data File ZaictureClick here for the Excel Score File a$.$ Report the accuracy, specificity, sensitivity$,$ and precision for the validation data set. $($Enter your answers as decimals and round them to $2$ decimal places.$)$b$-1.$ What is the area under the ROC curve $($or the AUC valuel? $($Round your answer to $4$ decimal places.$)$ b$\mathrm{.}2.$ Is the following statement a true statement? The ROC curve shows that in general the naive Bayes model performs better than the baseline model in terms sensitivity and specificity. True Faise c$.$ Report the scoring results for the five new observations. $\backslash$times $1\backslash$times $2$

A $0$

B $1$

C $1$

B $0$

C $0$