[[ml-get-influencer]] ==== Get Influencers The get influencers API enables you to retrieve information about the influencers in a job. ===== Request `GET _xpack/ml/anomaly_detectors//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. //TBD: Using the "sort" value? `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. `from`:: (integer) Skips the specified number of influencers. `influencer_score`:: (double) Returns influencers with anomaly scores higher than this value. `size`:: (integer) Specifies the maximum number of influencers to obtain. `sort`:: (string) Specifies the sort field for the requested influencers. //TBD: By default the results are sorted on the influencer score? `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 <>. ===== 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 <> and <>. ===== 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, "sequence_num": 2, "bucket_span": 600, "is_interim": false, "timestamp": 1454943600000 }, ... ] } ----