> ## Documentation Index
> Fetch the complete documentation index at: https://docs.startree.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# MATRIX_PROFILE

<Info>
  Enterprise only
</Info>

Gives an anomaly score to each point using a left matrix profile algorithm(^1). 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]\[iso-8601]   format. Requires `component.monitoringGranularity`, [see shared parameters](./#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](./#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

```json theme={null}
{
      "name": "root",
      "type": "AnomalyDetector",
      "params": {
        "type": "MATRIX_PROFILE",
        "component.sensitivity": "2",
        "component.lookbackPeriod": "P21D",
        ...  # shared parameters
      },
      "inputs": [
        {
          "targetProperty": "current",
          "sourcePlanNode": "currentData",
          "sourceProperty": "currentOutput"
        }
      ],
      "outputs": []
    }
```

(^1): See [https://www.cs.ucr.edu/\~eamonn/MatrixProfile.html](https://www.cs.ucr.edu/~eamonn/MatrixProfile.html)

[iso-8601](https://en.wikipedia.org/wiki/ISO_8601#Durations)