Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study

Detection of anomalous situations for complex mission-critical systems holds paramount importance when their service continuity needs to be ensured. A major challenge in detecting anomalies from the operational data arises due to the imbalanced class distribution problem since the anomalies are supposed to be rare events. This paper evaluates a diverse array of machine learning-based anomaly detection algorithms through a comprehensive benchmark study. The paper contributes significantly by conducting an unbiased comparison of various anomaly detection algorithms, spanning classical machine …

anomaly anomaly detection benchmarking challenge class continuity cs.lg data deep learning detection distribution events importance major mission service study systems tree