🌟 Fraud Detection in Application 🌟 Through Isolation Forest and K-Means Clustering, the project detects suspicious patterns like inconsistent income, duplicate entries, and unrealistic employment data. This end-to-end workflow transforms raw data into actionable fraud insights — enhancing trust and accuracy.
python export reporting scikit-learn exploratory-data-analysis data-import pandas seaborn pca matplotlib scaling data-normalization data-cleaning model-evaluation interpretation anomaly-detection csv-handling data-exporting
-
Updated
Nov 15, 2025 - Python