ShubhamS2005/FraudAnomalyDetection

This project uses unsupervised clustering via DBSCAN to detect fraudulent transactions without any prior labeling. By leveraging Z-score standardization, PCA for visualization, and cluster evaluation metrics, we create an effective and interpretable anomaly detection pipeline.