Please help me $$implement $($In C$++)$a Naive Bayes Classifier to classify individuals as either Democrats or Republicans using the $16$attributes and two classes from the Congressional Voting Records dataset.

Some of the attributes contain the value $"?",$which denotes a missing value. In this dataset, however, the $"?"$symbol explicitly means neither "yes" nor $"$no$",$i$.$e$.,$it represents a third option: "abstained". I should approach the problem in two ways:

Treat the $"?"$value as the third option $($abstained$).$

Fill the missing values with an approach of your choice, and justify why you chose this method.

Analyze the results.

In the Naive Bayes Classifier, zero probabilities can occur, leading to inaccurate classifications. To address this issue, apply the necessary solutions, including "Laplace smoothing" and the use of logarithms. Test with different values of the smoothing parameter $,$which determines the degree of smoothing. Analyze the results.

For testing the algorithm, split the data into training and testing sets in an $80$:$20$ratio$.$Prior to splitting, shuffle the data. The split should be stratified to preserve the ratio of classes $(267$Democrats$,168$Republicans$)$in the resulting training and test sets.

The input should accept two possible values $-0$and $1$:

$0$means to process the data by treating the $"?"$values as a third option: abstained$.$

$1$means to fill the missing values $($indicated by $"?")$using a method you choose.

The output should include:

$-$The accuracy of the model on the training set $($trained and tested on it$).$

$-$The accuracy and standard deviation of the model using $10-$fold cross$-$validation on the training set.

$-$The accuracy of the model on the test set.

Example input:

$0$

Example output:

$1.$Train Set Accuracy:

$$Accuracy: $92\mathrm{.}80\%$

$10-$Fold Cross$-$Validation Results:

$$Accuracy Fold $1$: $92\mathrm{.}00\%$

$$Accuracy Fold $2$: $91\mathrm{.}50\%$

$$Accuracy Fold $3$: $90\mathrm{.}00\%$

$$Accuracy Fold $4$: $93\mathrm{.}00\%$

$$Accuracy Fold $5$: $91\mathrm{.}00\%$

$$Accuracy Fold $6$: $92\mathrm{.}50\%$

$$Accuracy Fold $7$: $93\mathrm{.}00\%$

$$Accuracy Fold $8$: $91\mathrm{.}50\%$

$$Accuracy Fold $9$: $92\mathrm{.}00\%$

$$Accuracy Fold $10$: $93\mathrm{.}50\%$

$$Average Accuracy: $92\mathrm{.}10\%$

$$Standard Deviation: $1\mathrm{.}10\%$

$2.$Test Set Accuracy:

$$Accuracy: $92\mathrm{.}50\%$

Important Notes:

$**$I am allowed to use data structures such as DataFrame in the solution.

$-$The solution should be authentic and not based on external answers.

$-$Avoid using pre$-$built STL functions, and rely only on the most basic and necessary libraries for data structures and algorithms.

Here are the first $3$rows $($of $436$total$)$of the house$-$votes$-84.$data file that you have to read from:

republican,n$,$y$,$n$,$y$,$y$,$y$,$n$,$n$,$n$,$y$,?,$y$,$y$,$y$,$n$,$y

democrat,y$,$y$,$y$,$n$,$n$,$n$,$y$,$y$,$y$,$n$,$y$,?,$n$,$n$,$n$,$y

republican,y$,$y$,$n$,$y$,$y$,$y$,$y$,$n$,$n$,$n$,$n$,$y$,$y$,$y$,$n$,$y