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This project focuses on developing a robust fraud detection system using machine learning algorithms. It compares the performance of two popular ensemble methods: Random Forest and XGBoost, in classifying financial transactions as fraudulent or legitimate. The models are trained and evaluated on a real-world financial dataset.
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ldamasio/Financial-Fraud-Detection-RF-XGBoost
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This project focuses on developing a robust fraud detection system using machine learning algorithms. It compares the performance of two popular ensemble methods: Random Forest and XGBoost, in classifying financial transactions as fraudulent or legitimate. The models are trained and evaluated on a real-world financial dataset.
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