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 [HTML] [HTML] 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] Written Assignment:Project #4 - Unsupervised Learning Algorithm -Part II Choose a categorical feature variable and regroup it to make a binary categorical variable such that the small category contains less than 10% of the sample size. Perform a similar analysis as demonstrated in the case study in the lecture note. Due: Thursday, 12/12/2024