OpenSearch/docs/reference/ml/apis/get-influencer.asciidoc

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[role="xpack"]
[testenv="platinum"]
[[ml-get-influencer]]
=== Get influencers API
++++
<titleabbrev>Get influencers</titleabbrev>
++++
Retrieves job results for one or more influencers.
==== Request
`GET _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 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
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 _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
},
...
]
}
----