Types
DynamicThreshold
Dynamic Thresholds use a combination of smart algorithms to automatically detect anomalies in your data. The threshold model infers trends, seasonality, and peaks, and also adapts to shifts in your data. It learns from historical data and is trained on new data, continuously improving as more data is read. See the documentation for more information.
object
DynamicThresholdFields
adaptionRate
decisionBoundsType
The decision bound type on the dynamic threshold specifies whether the boundaries for anomaly detection are double or single-sided.
sensitivity
Float!
Sensitivity defines the accepted range of values for the dynamic threshold.