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KPI anomaly detection is one important function of network management system.Traditional methods either require prior knowledge or manually set thresholds.To overcome these shortcomings, we propose the Ensemble2 framework, whichapplies ensemble learning to improve exogenous capabilities. Meanwhile,automatically adjusts thresholds based on extreme value theory. The model istested on production datasets to verify its effectiveness. We further optimizethe model using online learning, and finally running at a speed of ~10 pts/s onan Intel i5 platform.

Ensemble2: Anomaly Detection via EVT-Ensemble Framework for Seasonal KPIs in Communication Network