please help

$\%$ Step $1$: Data Exploration and Preprocessing

$\%$ Load the dataset

data $=$ readtable$(\text{'}$creditcard$\_$csv$.$csv$\text{'})$; $\%$ Assuming the dataset is saved as 'creditcard.csv$\text{'}$

$\%$ Display basic information about the dataset

summary$($data$)$

$\%$ Select features $($Assuming $\text{'}$V$1\text{'}$ to $\text{'}$V$28\text{'}$ are the features$)$

features $=$ data$($:$,\{\text{'}$V$1\text{'},\text{'}$V$2\text{'},\text{'}$V$3\text{'},\text{'}$V$4\text{'},\text{'}$V$5\text{'},$ 'Class'$\})$;

$\%$ Step $2$: Split the data into training and testing sets

cv $=$ cvpartition$($size$($features$,1),$ 'HoldOut', $0\mathrm{.}2)$; $\%80\%$ train, $20\%$ test

idxTrain $=$ training$($cv$)$;

idxTest $=$ test$($cv$)$;

$\%$ Separate features and labels

X$\_$train $=$ features$\{$idxTrain$,1$:end$-1\}$;

Y$\_$train $=$ features$\{$idxTrain$,$ end$\}$;

X$\_$test $=$ features$\{$idxTest$,1$:end$-1\}$;

Y$\_$test $=$ features$\{$idxTest$,$ end$\}$;

$\%$ Step $2($continued$)$: Model Training and Evaluation

$\%$ Train models using Classification Learner App

$\%$ Make sure to export the model with the highest accuracy

$\%$ After training, export the model with the highest accuracy to MATLAB workspace

$\%$ Replace 'YourBestModel' with the variable name of your best model

$\%$ Ensure to replace 'YourModelName' with a descriptive name for your model

$\%$ Example:

$\%$ exportModel$($YourBestModel$,$ 'YourModelName'$)$;

$\%$ Step $3$: Testing and Evaluation

$\%$ Evaluate the models using testing data

$\%$ Y$\_$pred $=$ predict$($best$123,$ X$\_$test$)$;

Y$\_$pred $=$ YourBestModel.predictFcn$($X$\_$test$)$;

$\%$ Calculate accuracy

$\%$accuracy $=$ sum$($Y$\_$pred $==$ Y$\_$test$)/$ numel$($Y$\_$test$)$;

$\%$ Calculate accuracy

accuracy $=$ sum$($strcmp$($Y$\_$pred, Y$\_$test$))/$ numel$($Y$\_$test$)$;

$\%$ Display confusion matrix

confMat $=$ confusionmat$($Y$\_$test, Y$\_$pred$)$;

disp$($confMat$)$;

$\%$ Step $3$: Application Development

$\%$ Open MATLAB App Designer and create a new app

$\%$ Design the UI with necessary components like buttons, axes, etc.

$\%$ Implement functionality to upload test features, predict classes, and display the confusion matrix

$\%$ Ensure creativity and use of unique widgets as per requirements

$\%$ Provide explanations for the app design and code is this code correct for task $1\mathrm{.}1$ if not please fix it and send full answer please

Question $1$:

MATLAB

$1\mathrm{.}1$ Developing the Machine Learning Model

Note:, select only $5$ features out of the available columns

Credit Card Fraud Detection Dataset

data set file name $($ creditcard$\_$csv$.$csv $)$

Train$-$Test Split: $80\%-20\%$

Output: Output $(1$ or $0)$

train and compare $5$ machine learning models for the specific application using the Matlab Classification Learner App. Ensure to export the model with the highest accuracy.

make sure to include these in your code:

Introduction

Database Loading, Pre$-$processing, and Train$-$test split

Training process Screenshot and Training Results

Testing, Confusion Matrix, accuracy, and saved model

Explanations for each step

Conclusion

$1\mathrm{.}2$ Developing the Application or Website

Using the model that you saved in Task $1,$ use Matlab App Designer. to create a user interface application that satisfies the following requirements:

a$)$ Allows the user to upload test features.

c$)$ Implements the model saved in Task $1$ to determine the class of the features uploaded.

d$)$ Provides an option to display the confusion matrix in Task $1$ within a separate Axes.

e$)$ Ensure creativity and use of unique widgets

f$)$ Explanation of the app design and code