OFFSET_AGGREGATION

Enterprise only

Compares current value to the value predicted by a naive model. The naive model is an average/median/percentile of historical values. The upper/lower bounds interval can be computed with an absolute or a percentage rule.

Inputs

"targetProperty": "current": The data on which to perform detection.

Parameters

name	description	default value
`component.intervalsMethod`	Method to compute intervals. In `PERCENTAGE`, `ABSOLUTE`.
`component.sensitivity`	Detection sensitivity. Eg with `PERCENTAGE`, set 50 for a 50% percentage change threshold.
`component.lookbackPeriod`	Historical period to use for training. In ISO-8601 format. Requires `component.monitoringGranularity`, see shared parameters. Eg: `P14D`.
`component.offsets`	A list of offsets in ISO-8601 format to use as baseline. Eg [`P7D`, `P14D`] will compare the current value to the aggregation of the values of the 2 previous weeks.	`[P7D]`
`component.aggregation`	The aggregation function to use to combine historical values. In `MEDIAN`, `AVERAGE`, `MIN`, `MAX` and any of `PCTXXXXX` eg `PCT05` (5th percentile), `PCT95`, `PCT999` (99.9th percentile).	`AVERAGE`

offsets and lookbackPeriod must be compatible. Eg if offsets is [P7D, P14D] then lookbackPeriod should be at least P14D.

Example

{
  "name": "root",
  "type": "AnomalyDetector",
  "params": {
    "type": "OFFSET_AGGREGATION",
    "component.intervalsMethod": "ABSOLUTE",
    "component.sensitivity": "200",  # detect if abs(current-predicted)>200
    "component.lookbackPeriod": "P28D",
    "component.offsets": ["P7D", "P14D", "P21D", "P28D"],
    "component.aggregation": "MEDIAN"
  },
  "inputs": [
    {   # current data
      "targetProperty": "current",
      "sourcePlanNode": "currentData",
      "sourceProperty": "currentOutput"
    }
  ]
}

iso-8601

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