Get influencers API

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Retrieves job results for one or more influencers.

Request

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GET _xpack/ml/anomaly_detectors/<job_id>/results/influencers

Path Parameters

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job_id
(string) Identifier for the job.

Request Body

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desc
(boolean) If true, the results are sorted in descending order.
end
(string) Returns influencers with timestamps earlier than this time.
exclude_interim
(boolean) If true, the output excludes interim results. By default, interim results are included.
influencer_score
(double) Returns influencers with anomaly scores greater or equal than this value.
page
from
(integer) Skips the specified number of influencers.
size
(integer) 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) Returns influencers with timestamps after this time.

Results

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The API returns the following information:

influencers
(array) An array of influencer objects. For more information, see Influencers.

Authorization

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You must have monitor_ml, monitor, manage_ml, or manage cluster privileges to use this API. You also need read index privilege on the index that stores the results. The machine_learning_admin and machine_learning_user roles provide these privileges. For more information, see Security privileges and Built-in roles.

Examples

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The following example gets influencer information for the it_ops_new_kpi job:

GET _xpack/ml/anomaly_detectors/it_ops_new_kpi/results/influencers
{
  "sort": "influencer_score",
  "desc": true
}

In this example, the API returns the following information, sorted based on the influencer score in descending order:

{
  "count": 28,
  "influencers": [
    {
      "job_id": "it_ops_new_kpi",
      "result_type": "influencer",
      "influencer_field_name": "kpi_indicator",
      "influencer_field_value": "online_purchases",
      "kpi_indicator": "online_purchases",
      "influencer_score": 94.1386,
      "initial_influencer_score": 94.1386,
      "probability": 0.000111612,
      "bucket_span": 600,
      "is_interim": false,
      "timestamp": 1454943600000
    },
  ...
  ]
}