Get anomaly detection job results for influencers Added in 5.4.0

GET /_ml/anomaly_detectors/{job_id}/results/influencers

Influencers are the entities that have contributed to, or are to blame for, the anomalies. Influencer results are available only if an influencer_field_name is specified in the job configuration.

Path parameters

  • job_id string Required

    Identifier for the anomaly detection job.

Query parameters

  • desc boolean

    If true, the results are sorted in descending order.

  • end string | number

    Returns influencers with timestamps earlier than this time. The default value means it is unset and results are not limited to specific timestamps.

  • exclude_interim boolean

    If true, the output excludes interim results. By default, interim results are included.

  • influencer_score number

    Returns influencers with anomaly scores greater than or equal to this value.

  • from number

    Skips the specified number of influencers.

  • size number

    Specifies the maximum number of influencers to obtain.

  • sort string

    Specifies the sort field for the requested influencers. By default, the influencers are sorted by the influencer_score value.

  • start string | number

    Returns influencers with timestamps after this time. The default value means it is unset and results are not limited to specific timestamps.

application/json

Body

  • page object

    Additional properties are allowed.

    Hide page attributes Show page attributes object
    • from number

      Skips the specified number of items.

    • size number

      Specifies the maximum number of items to obtain.

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • count number Required
    • influencers array[object] Required

      Array of influencer objects

      Hide influencers attributes Show influencers attributes object
      • bucket_span number

        Time unit for seconds

      • influencer_score number Required

        A normalized score between 0-100, which is based on the probability of the influencer in this bucket aggregated across detectors. Unlike initial_influencer_score, this value is updated by a re-normalization process as new data is analyzed.

      • influencer_field_name string Required

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

      • influencer_field_value string Required

        The entity that influenced, contributed to, or was to blame for the anomaly.

      • initial_influencer_score number Required

        A normalized score between 0-100, which is based on the probability of the influencer aggregated across detectors. This is the initial value that was calculated at the time the bucket was processed.

      • is_interim boolean Required

        If true, this is an interim result. In other words, the results are calculated based on partial input data.

      • job_id string Required
      • probability number Required

        The probability that the influencer has this behavior, in the range 0 to 1. This value can be held to a high precision of over 300 decimal places, so the influencer_score is provided as a human-readable and friendly interpretation of this value.

      • result_type string Required

        Internal. This value is always set to influencer.

      • timestamp number

        Time unit for milliseconds

      • foo string

        Additional influencer properties are added, depending on the fields being analyzed. For example, if it’s analyzing user_name as an influencer, a field user_name is added to the result document. This information enables you to filter the anomaly results more easily.
GET /_ml/anomaly_detectors/{job_id}/results/influencers 
curl \
 -X GET http://api.example.com/_ml/anomaly_detectors/{job_id}/results/influencers \
 -H "Content-Type: application/json" \
 -d '{"page":{"from":42.0,"size":42.0}}'
Request examples 
{
  "page": {
    "from": 42.0,
    "size": 42.0
  }
}
Response examples (200) 
{
  "count": 42.0,
  "influencers": [
    {
      "": 42.0,
      "influencer_score": 42.0,
      "influencer_field_name": "string",
      "influencer_field_value": "string",
      "initial_influencer_score": 42.0,
      "is_interim": true,
      "job_id": "string",
      "probability": 42.0,
      "result_type": "string",
      "foo": "string"
    }
  ]
}