Please write the following code properly in C$++$ programming language:

#include #include #include #include #include #define MAX$\_$ROWS $435$ #define MAX$\_$COLS $17$ #define MAX$\_$CLASS $2//$ Define classes #define DEMOCRAT $0$ #define REPUBLICAN $1//$ Define votes #define YEA $1$ #define NAY $0$ #define ABSTAIN $2//$ Data structure for the dataset typedef struct $\{$ int class; int attributes$[$MAX$\_$COLS $-1]$; $\}$ Record; Record data$[$MAX$\_$ROWS$]$; int total$\_$records $=0$; $//$ Function to read the dataset void read$\_$data$($const char $*$filename$,$ int treat$\_$missing$\_$as$\_$abstain$)\{$ FILE $*$file $=$ fopen$($filename$,"$r$")$; if $(!$file$)\{$ perror$("$Error opening file"$)$; exit$($EXIT$\_$FAILURE$)$; $\}$ char line$[256]$; total$\_$records $=0$; while $($fgets$($line$,$ sizeof$($line$),$ file$))\{$ char $*$token $=$ strtok$($line$,",")$; data$[$total$\_$records$].$class $=$ strcmp$($token$,$ "democrat"$)==0?$ DEMOCRAT : REPUBLICAN; for $($int i $=0$; i $<$ MAX$\_$COLS $-1$; i$++)\{$ token $=$ strtok$($NULL$,",")$; if $($strcmp$($token$,"$y$")==0)\{$ data$[$total$\_$records$].$attributes$[$i$]=$ YEA; $\}$ else if $($strcmp$($token$,"$n$")==0)\{$ data$[$total$\_$records$].$attributes$[$i$]=$ NAY; $\}$ else $\{$ data$[$total$\_$records$].$attributes$[$i$]=$ treat$\_$missing$\_$as$\_$abstain $?$ ABSTAIN : $-1$; $\}\}$ total$\_$records$++$; $\}$ fclose$($file$)$; $\}//$ Function to shuffle data void shuffle$\_$data$($Record $*$data$,$ int n$)\{$ srand$($time$($NULL$))$; for $($int i $=$ n $-1$; i $>0$; i$--)\{$ int j $=$ rand$()\%($i $+1)$; Record temp $=$ data$[$i$]$; data$[$i$]=$ data$[$j$]$; data$[$j$]=$ temp; $\}\}//$ Function to stratify split the data void stratified$\_$split$($Record $*$data$,$ int total, Record $*$train$,$ int $*$train$\_$size, Record $*$test$,$ int $*$test$\_$size, double split$\_$ratio$)\{$ int democrat$\_$count $=0,$ republican$\_$count $=0$; for $($int i $=0$; i $<$ total; i$++)\{$ if $($data$[$i$].$class $==$ DEMOCRAT$)$ democrat$\_$count$++$; else republican$\_$count$++$; $\}$ int train$\_$democrats $=$ democrat$\_$count $*$ split$\_$ratio; int train$\_$republicans $=$ republican$\_$count $*$ split$\_$ratio; int democrat$\_$added $=0,$ republican$\_$added $=0$; $*$train$\_$size $=*$test$\_$size $=0$; for $($int i $=0$; i $<$ total; i$++)\{$ if $($data$[$i$].$class $==$ DEMOCRAT && democrat$\_$added $<$ train$\_$democrats$)\{$ train$[(*$train$\_$size$)++]=$ data$[$i$]$; democrat$\_$added$++$; $\}$ else if $($data$[$i$].$class $==$ REPUBLICAN && republican$\_$added $<$ train$\_$republicans$)\{$ train$[(*$train$\_$size$)++]=$ data$[$i$]$; republican$\_$added$++$; $\}$ else $\{$ test$[(*$test$\_$size$)++]=$ data$[$i$]$; $\}\}\}//$ Function to calculate probabilities with Laplace smoothing void calculate$\_$probabilities$($Record $*$train$,$ int train$\_$size, double probabilities$[$MAX$\_$CLASS$][$MAX$\_$COLS $-1][3],$ double class$\_$priors$[$MAX$\_$CLASS$],$ double lambda$)\{$ int class$\_$counts$[$MAX$\_$CLASS$]=\{0\}$; for $($int c $=0$; c $<$ MAX$\_$CLASS; c$++)\{$ for $($int i $=0$; i $<$ MAX$\_$COLS $-1$; i$++)\{$ for $($int v $=0$; v $<3$; v$++)\{$ probabilities$[$c$][$i$][$v$]=$ lambda; $\}\}\}$ for $($int i $=0$; i $<$ train$\_$size; i$++)\{$ class$\_$counts$[$train$[$i$].$class$]++$; for $($int j $=0$; j $<$ MAX$\_$COLS $-1$; j$++)\{$ if $($train$[$i$].$attributes$[$j$]!=-1)\{$ probabilities$[$train$[$i$].$class$][$j$][$train$[$i$].$attributes$[$j$]]++$; $\}\}\}$ for $($int c $=0$; c $<$ MAX$\_$CLASS; c$++)\{$ class$\_$priors$[$c$]=($double$)$class$\_$counts$[$c$]/$ train$\_$size; for $($int i $=0$; i $<$ MAX$\_$COLS $-1$; i$++)\{$ double total $=$ class$\_$counts$[$c$]+3*$ lambda; for $($int v $=0$; v $<3$; v$++)\{$ probabilities$[$c$][$i$][$v$]/=$ total; $\}\}\}\}//$ Function to predict using Naive Bayes int naive$\_$bayes$\_$predict$($Record $*$record$,$ double probabilities$[$MAX$\_$CLASS$][$MAX$\_$COLS $-1][3],$ double class$\_$priors$[$MAX$\_$CLASS$])\{$ double log$\_$probs$[$MAX$\_$CLASS$]=\{$log$($class$\_$priors$[$DEMOCRAT$]),$ log$($class$\_$priors$[$REPUBLICAN$])\}$; for $($int c $=0$; c $<$ MAX$\_$CLASS; c$++)\{$ for $($int i $=0$; i $<$ MAX$\_$COLS $-1$; i$++)\{$ if $($record$->$attributes$[$i$]!=-1)\{$ log$\_$probs$[$c$]+=$ log$($probabilities$[$c$][$i$][$record$->$attributes$[$i$]])$; $\}\}\}$ return log$\_$probs$[$DEMOCRAT$]>$ log$\_$probs$[$REPUBLICAN$]?$ DEMOCRAT : REPUBLICAN; $\}//$ Function to evaluate model accuracy void evaluate$\_$model$($Record $*$data$,$ int size, double probabilities$[$MAX$\_$CLASS$][$MAX$\_$COLS $-1][3],$ double class$\_$priors$[$MAX$\_$CLASS$],$ double $*$accuracy$)\{$ int correct $=0$; for $($int i $=0$; i $<$ size; i$++)\{$ if $($naive$\_$bayes$\_$predict$($&data$[$i$],$ probabilities, class$\_$priors$)==$ data$[$i$].$class$)\{$ correct$++$; $\}\}*$accuracy $=($double$)$correct $/$ size; $\}//$ Function for $10-$fold cross$-$validation void