12. Algorithms for Anomaly Detection

Topics, Class Notes and Code		Assignments and Side Readings
Anomaly Detection Use Cases Algorithms and Models for Anomaly Detection Supervised Anomaly Detection Unsupervised Anomaly Detection Local Outlier Factor (LOF) Some Distances and Related Terms Steps for Defining LOF Scores Fraud Dtection with LOF - Case Study LOF As A Standalone Algorithm: Hyperparameter Tuning and Performance Measures LOF As A Feature Extraction Algorithm Notes and Code Class Note: [HTML] [PDF] Original LOF Paper [PDF]		Optonal Reading Assignments A Good Survey of Anomaly Detection Algorithms [PDF] pROC Help Documentation [PDF] Additional Fraud Data for Practice [Web Link] Project Three: Unsupervized Feature Extraction Outline [link] Part II - Local Outlier Factor Select all numerical variables in the analytical data set to find LOF Perform the binary clssification analysis by adding the new LOF to the model. Due: Tuesday, 12/25/2025