107 lines
2.6 KiB
Plaintext
107 lines
2.6 KiB
Plaintext
[[ml-get-influencer]]
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==== Get Influencers
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The get influencers API enables you to retrieve information about the influencers
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in a job.
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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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//TBD: Using the "sort" value?
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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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`from`::
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(integer) Skips the specified number of influencers.
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`influencer_score`::
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(double) Returns influencers with anomaly scores higher than this value.
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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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//TBD: By default the results are sorted on the influencer score?
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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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<<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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"sequence_num": 2,
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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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