Overview

The anomaly detection module implements time series data based on statistics methods to detect possible exceptions in the data. The framework of this module is decoupled to flexibly replace different anomaly detection algorithms. In addition, this module can automatically select algorithms based on different features of time series data. It supports anomaly value detection, threshold detection, box plot detection, gradient detection, growth rate detection, fluctuation rate detection, and status conversion detection.