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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.
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Merge pull request #4 from vijaysrivastava12568/patch-1
9997b1dView on GitHubMerge pull request #2 from vijaysrivastava12568/master
bdd8823View on GitHubMerge pull request #1 from vijaysrivastava12568/readme_update_patch_1
2bcff28View on GitHubMerge branch 'master' of https://github.com/ShubhamS2005/FraudAnomalyDetection
9ba4557View on GitHub