📄️ Anomaly detection algorithms
The anomaly detection machine learning features use a bespoke amalgamation of different techniques such as clustering, various types of time series decomposition, Bayesian distribution modeling, and correlation analysis. These analytics provide sophisticated real-time automated anomaly detection for time series data.
📄️ Anomaly score explanation
Every anomaly has an anomaly score assigned to it. That score indicates how anomalous the data point is, which makes it possible to define its severity compared to other anomalies. This page gives you a high-level explanation of the critical factors considered for calculating anomaly scores, how the scores are calculated, and how renormalization works.
📄️ Job types
Anomaly detection job types