Unsupervised anomaly detection ensembles using item response theory

Ensemble learning combines many algorithms or models to obtain better predictive performance. Ensembles have produced the winning algorithm in competitions such as the Netflix Prize. They are used in climate modeling and relied upon to make daily forecasts. Constructing an ensemble from a heterogeneous set of unsupervised anomaly detection methods presents challenges because the class labels or the ground truth is unknown. Thus, traditional ensemble techniques that use the class labels cannot be used for this task.