Credit card fraud detection in R language

Credit card fraud detection project uses machine learning and r programming concept.
The aim of the project is to build a classifier that can detect credit card fraud transaction using variety of machine learning algorithm that will be able to detect fraudulent and non fraudulent transactions and compare the results on parameters such as Accuracy,recall,precision and ROC.

To Do:
An user interface is required to test and train data using R programming language.
Train and test button are needed to be added in the gui such that when user click on train the five algorithm are required to train the dataset and on click on test button it will take to another window where input is given by user and output needs to be display as fraud or non fraud.
Use classifiers:Naive Bayes,logistics regression,Random Forest, Decision Tree and XGboost.

Use Dataset:https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud

Reference Paper:https://www.ijert.org/research/credit-card-fraud-detection-using-machine-learning-algorithms-IJERTV9IS070649.pdf