111 lines
2.7 KiB
Plaintext
111 lines
2.7 KiB
Plaintext
[role="xpack"]
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[testenv="platinum"]
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[[ml-get-influencer]]
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=== Get Influencers API
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++++
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<titleabbrev>Get Influencers</titleabbrev>
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++++
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Retrieves job results for one or more influencers.
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==== Request
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`GET _xpack/ml/anomaly_detectors/<job_id>/results/influencers`
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//===== Description
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==== Path Parameters
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`job_id`::
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(string) Identifier for the job.
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==== Request Body
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`desc`::
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(boolean) If true, the results are sorted in descending order.
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`end`::
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(string) Returns influencers with timestamps earlier than this time.
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`exclude_interim`::
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(boolean) If true, the output excludes interim results.
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By default, interim results are included.
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`influencer_score`::
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(double) Returns influencers with anomaly scores greater or equal than this value.
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`page`::
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`from`:::
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(integer) Skips the specified number of influencers.
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`size`:::
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(integer) Specifies the maximum number of influencers to obtain.
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`sort`::
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(string) Specifies the sort field for the requested influencers.
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By default the influencers are sorted by the `influencer_score` value.
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`start`::
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(string) Returns influencers with timestamps after this time.
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==== Results
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The API returns the following information:
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`influencers`::
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(array) An array of influencer objects.
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For more information, see <<ml-results-influencers,Influencers>>.
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==== Authorization
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You must have `monitor_ml`, `monitor`, `manage_ml`, or `manage` cluster
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privileges to use this API. You also need `read` index privilege on the index
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that stores the results. The `machine_learning_admin` and `machine_learning_user`
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roles provide these privileges. For more information, see
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{xpack-ref}/security-privileges.html[Security Privileges] and
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{xpack-ref}/built-in-roles.html[Built-in Roles].
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//<<security-privileges>> and <<built-in-roles>>.
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==== Examples
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The following example gets influencer information for the `it_ops_new_kpi` job:
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[source,js]
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--------------------------------------------------
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GET _xpack/ml/anomaly_detectors/it_ops_new_kpi/results/influencers
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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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// CONSOLE
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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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[source,js]
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----
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{
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"count": 28,
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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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]
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}
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----
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