Designing Anomaly Detection Algorithms that Exploit Flexible Supervision KU Leuven
Anomaly detection is the task of identifying observations in a dataset that do not conform the expected behavior. It is a crucial data mining task as in the real world, anomalous observations often correspond to real costs. For example, a machine that breaks, a fraudulent credit card transaction, or a patient experiencing irregular heart rhythms. With the advent of big data, manually sifting through millions of observations to detect the ...