Fraud Detection Project

This is my MCA project to find fraud in credit card transactions using AI. I used Python with Logistic Regression and SMOTE. The final F1 score is 77.51%, which means it catches most frauds with fewer mistakes.

Files in This Project

• scripts/: Has the code files (.py) to run the project.
• outputs/: Has the pictures (.png) like graphs and charts showing the results.
• about.txt: Explains more about the project.

How to Get the Data File (creditcard.csv)

The project needs a file called creditcard.csv, but it’s too big to upload here. You can download it from this website:

• Go to Kaggle Credit Card Fraud Detection.
• Download the creditcard.csv file (you might need a free Kaggle account).
• Save the creditcard.csv file in the main folder of this project (not inside scripts/ or outputs/, but next to them).

How to Run the Project

1. Download all the files from this repository.
2. Put the creditcard.csv file in the main folder.
3. Install Python on your computer.
4. Install these tools using the terminal : pip install pandas pip install numpy pip install scikit-learn pip install imblearn pip install matplotlib pip install seaborn
5. Go to the scripts/ folder and run the files in this order : python preprocess.py python train_model.py python train_smote.py python train_smote_threshold.py python f1_comparison.py python more_plots.py python workflow_comparison.py python system_design_flowchart.py
6. Check the outputs/ folder for the pictures showing the results !