2017-06-19 21:23:58 -04:00
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[role="xpack"]
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2018-08-31 19:49:24 -04:00
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[testenv="platinum"]
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2017-04-04 18:26:39 -04:00
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[[ml-get-influencer]]
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2018-12-20 13:23:28 -05:00
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=== Get influencers API
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2017-12-14 13:52:49 -05:00
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++++
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2018-12-20 13:23:28 -05:00
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<titleabbrev>Get influencers</titleabbrev>
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++++
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Retrieves {anomaly-job} results for one or more influencers.
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2019-06-27 12:42:47 -04:00
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[[ml-get-influencer-request]]
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==== {api-request-title}
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2017-04-04 18:26:39 -04:00
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2018-12-07 15:34:11 -05:00
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`GET _ml/anomaly_detectors/<job_id>/results/influencers`
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2019-06-27 16:58:42 -04:00
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[[ml-get-influencer-prereqs]]
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==== {api-prereq-title}
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* If the {es} {security-features} are enabled, you must have `monitor_ml`,
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`monitor`, `manage_ml`, or `manage` cluster privileges to use this API. You also
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need `read` index privilege on the index that stores the results. The
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`machine_learning_admin` and `machine_learning_user` roles provide these
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privileges. See {stack-ov}/security-privileges.html[Security privileges] and
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{stack-ov}/built-in-roles.html[Built-in roles].
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2019-06-27 12:42:47 -04:00
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[[ml-get-influencer-path-parms]]
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==== {api-path-parms-title}
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2019-07-12 11:26:31 -04:00
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`<job_id>`::
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(Required, string) Identifier for the {anomaly-job}.
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2019-06-27 12:42:47 -04:00
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[[ml-get-influencer-request-body]]
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==== {api-request-body-title}
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2017-04-10 19:14:26 -04:00
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2019-07-12 11:26:31 -04:00
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`desc`::
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(Optional, boolean) If true, the results are sorted in descending order.
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2019-07-12 11:26:31 -04:00
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`end`::
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(Optional, string) Returns influencers with timestamps earlier than this time.
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2017-04-10 19:14:26 -04:00
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2019-07-12 11:26:31 -04:00
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`exclude_interim`::
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(Optional, boolean) If true, the output excludes interim results. By default,
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interim results are included.
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2017-04-24 13:46:17 -04:00
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2019-07-12 11:26:31 -04:00
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`influencer_score`::
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(Optional, double) Returns influencers with anomaly scores greater than or
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equal to this value.
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2019-07-12 11:26:31 -04:00
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`page`::
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`from`:::
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(Optional, integer) Skips the specified number of influencers.
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`size`:::
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(Optional, integer) Specifies the maximum number of influencers to obtain.
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2017-04-10 19:14:26 -04:00
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2019-07-12 11:26:31 -04:00
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`sort`::
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(Optional, string) Specifies the sort field for the requested influencers. By
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default, the influencers are sorted by the `influencer_score` value.
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2017-04-04 18:26:39 -04:00
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2019-07-12 11:26:31 -04:00
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`start`::
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(Optional, string) Returns influencers with timestamps after this time.
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2017-04-04 18:26:39 -04:00
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2019-06-27 12:42:47 -04:00
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[[ml-get-influencer-results]]
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==== {api-response-body-title}
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2017-04-10 19:14:26 -04:00
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The API returns the following information:
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2017-04-04 18:26:39 -04:00
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2017-04-10 19:14:26 -04:00
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`influencers`::
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(array) An array of influencer objects.
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2017-04-10 19:14:26 -04:00
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For more information, see <<ml-results-influencers,Influencers>>.
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2017-04-04 18:26:39 -04:00
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2019-06-27 12:42:47 -04:00
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[[ml-get-influencer-example]]
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==== {api-examples-title}
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2017-04-04 18:26:39 -04:00
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2017-04-10 19:14:26 -04:00
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The following example gets influencer information for the `it_ops_new_kpi` job:
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2019-09-06 11:31:13 -04:00
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[source,console]
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2017-04-10 19:14:26 -04:00
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--------------------------------------------------
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2018-12-07 15:34:11 -05:00
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GET _ml/anomaly_detectors/it_ops_new_kpi/results/influencers
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2017-04-10 19:14:26 -04:00
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{
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"sort": "influencer_score",
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"desc": true
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}
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--------------------------------------------------
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// TEST[skip:todo]
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In this example, the API returns the following information, sorted based on the
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influencer score in descending order:
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2017-04-21 11:23:27 -04:00
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[source,js]
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2017-04-04 18:26:39 -04:00
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----
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{
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"count": 28,
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2017-04-10 19:14:26 -04:00
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"influencers": [
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{
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"job_id": "it_ops_new_kpi",
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"result_type": "influencer",
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"influencer_field_name": "kpi_indicator",
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"influencer_field_value": "online_purchases",
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"kpi_indicator": "online_purchases",
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"influencer_score": 94.1386,
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"initial_influencer_score": 94.1386,
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"probability": 0.000111612,
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"bucket_span": 600,
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"is_interim": false,
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"timestamp": 1454943600000
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},
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...
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2017-04-04 18:26:39 -04:00
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]
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}
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----
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