Using R$,$ form a dataset with "yesno" as a dependent variable and the four following character variables: ; $([$ #

a$.$ Fit a classification tree selecting a complexity parameter of $0\mathrm{.}01$ and use set.seed$(4).$ Use the $4$ predictors to fit the outcome variable.

c$.$ Use the $$one standard deviation rule$(1$SD$)$ to decide if the tree obtained in $($b$)$ is optimal or not. Reduce the complexity parameter to $\mathrm{.}001$ if you did not attain a minimum XERROR for the rule from part $($b$).$ Again, using set.seed$(4)$ grow a tree and print the information on predictive accuracy with printcp and show your calculations. How many splits are in the optimal tree? If this classification tree is not the optimal tree according to $1$SD$,$ then prune it$,$ and plot the pruned tree with an optimal number of splits.