[role="xpack"]
[[ml-get-influencer]]
=== Get Influencers

The get influencers API enables you to retrieve job results for one or more
influencers.


==== Request

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

//===== Description

==== Path Parameters

`job_id`::
  (string) Identifier for the job.

==== Request Body

`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 higher 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

The API returns the following information:

`influencers`::
  (array) An array of influencer objects.
  For more information, see <<ml-results-influencers,Influencers>>.


==== Authorization

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
{xpack-ref}/security-privileges.html[Security Privileges] and
{xpack-ref}/built-in-roles.html[Built-in Roles].
//<<security-privileges>> and <<built-in-roles>>.


==== Examples

The following example gets influencer information for the `it_ops_new_kpi` job:

[source,js]
--------------------------------------------------
GET _xpack/ml/anomaly_detectors/it_ops_new_kpi/results/influencers
{
  "sort": "influencer_score",
  "desc": true
}
--------------------------------------------------
// CONSOLE
// TEST[skip:todo]

In this example, the API returns the following information, sorted based on the
influencer score in descending order:
[source,js]
----
{
  "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
    },
  ...
  ]
}
----