Selection of appropriate machine learning algorithms for credit card fraud detection. It’s important to identify the most suitable algorithm that demonstrates high accuracy.The Synthetic Minority Over-sampling Technique (SMOTE) is employed. This framework was evaluated with various methods such as Logistic Regression (LR), Random Forest (RF), Local Outlier Factor (LOF), Extreme Gradient Boosting (XGBoost), and Decision Tree (DT), coupled with Adaptive Boosting (AdaBoost), to ensure high accuracy in detecting fraudulent transactions

Step 1: Clone the repository

git clone https://github.com/rifatperween/credit-card-fraud-detection.git

Step 2: Open the first terminal

npm install
npm run dev

Step 3: Open second terminal

pipenv install
pipenv shell
python app.py