-Credit-Card-Fraud-Detection

Using Random Forest and SVM models

Credit Card Fraud Detection Model using Random Forest and SVM

This project aims to detect fraudulent credit card transactions using machine learning techniques such as Random Forest and Support Vector Machines (SVM).

Dataset

The dataset used is creditcard. The dataset is referenced from Kaggle.

Techniques Used

• Random Forest: Used for its ability to handle complex relationships and feature interactions.
• SVM: Chosen for its effectiveness in separating classes in high-dimensional spaces.

Model Performance

• Random Forest Accuracy: 99.87%
• SVM Accuracy: 99.88%

Conclusion

Both Random Forest and SVM showed promising results in detecting credit card fraud. SVM achieved higher accuracy, while Random Forest provided robust performance in separating fraudulent and non-fraudulent transactions.