MATRIX_PROFILE
💡
Enterprise only
Gives an anomaly score to each point using a left matrix profile algorithm1. To make the matrix profile approach better at point anomaly detection, a proprietary transformation function is applied to the matrix profile.
This detector returns an anomaly score, it does not return expected values, upper and lower bounds. This detector is recommended for granularity <= 1 hour.
Inputs
"targetProperty": "current": The data on which to perform detection. It should contain the historical data to use for training.
Parameters
| name | description | default value |
|---|---|---|
component.sensitivity | Anomaly score threshold. Eg for 0.8`` every point that has as a score bigger that 0.8` is flagged as an anomaly. | |
component.lookbackPeriod | Historical period to use as a reference. In ISO-8601 (opens in a new tab) format. Requires component.monitoringGranularity, see shared parameters. Eg: P14D. If component.lookbackPeriod is not set, component.lookback is used. | |
component.seasonalityPeriod | Seasonality biggest period. Used to infer the window size of the matrix profile. In ISO-8601 format. Requires component.monitoringGranularity, see shared parameters. Eg: P7D. | null (inferred from the data) |
component.distance | For advanced users. Whether to use NORMALIZED or NON_NORMALIZED euclidean distance for the matrix profile computation. | NORMALIZED |
component.computeBounds | Experimental. If true, attempts to compute expected values, upper and lower bounds. | false |
component.scoringMethod | Experimental. Experimental. Post-processing of the matrix profile anomaly scores. FIRST_ORDER_DIFFERENCE is good at detecting spikes. DIRECT is good at detecting drifts. | FIRST_ORDER_DIFFERENCE |
Example
Recommended defaults
{
"name": "root",
"type": "AnomalyDetector",
"params": {
"type": "MATRIX_PROFILE",
"component.sensitivity": "2",
"component.lookbackPeriod": "P21D",
... # shared parameters
},
"inputs": [
{
"targetProperty": "current",
"sourcePlanNode": "currentData",
"sourceProperty": "currentOutput"
}
],
"outputs": []
}