elasticsearch-js/docs/reference/api/MlInfluencer.md

MlInfluencer [interface-MlInfluencer]

Name	Type	Description
bucket_span	DurationValue<UnitSeconds>	The length of the bucket in seconds. This value matches the bucket span that is specified in the job.
foo	string	Additional influencer properties are added, depending on the fields being analyzed. For example, if it’s analyzing user_name as an influencer, a field user_name is added to the result document. This information enables you to filter the anomaly results more easily.
influencer_field_name	Field	The field name of the influencer.
influencer_field_value	string	The entity that influenced, contributed to, or was to blame for the anomaly.
influencer_score	double	A normalized score between 0-100, which is based on the probability of the influencer in this bucket aggregated across detectors. Unlike initial_influencer_score, this value is updated by a re-normalization process as new data is analyzed.
initial_influencer_score	double	A normalized score between 0-100, which is based on the probability of the influencer aggregated across detectors. This is the initial value that was calculated at the time the bucket was processed.
is_interim	boolean	If true, this is an interim result. In other words, the results are calculated based on partial input data.
job_id	Id	Identifier for the anomaly detection job.
probability	double	The probability that the influencer has this behavior, in the range 0 to 1. This value can be held to a high precision of over 300 decimal places, so the influencer_score is provided as a human-readable and friendly interpretation of this value.
result_type	string	Internal. This value is always set to influencer.
timestamp	EpochTime<UnitMillis>	The start time of the bucket for which these results were calculated.