This python program uses ml algorithms to flag a fradulent transaction.
To tackle this issue, the project uses two anomaly detection methods: •Isolation Forest (IF) •Local Outlier Factor (LOF)
The workflow consists of : •Data preprocessing •Feature scaling •Training the anomaly detection models •Evaluating performance with confusion matrices and classification reports