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

Interface MlDetectorRead

Name	Type	Description
by_field_name	Field	The field used to split the data. In particular, this property is used for analyzing the splits with respect to their own history. It is used for finding unusual values in the context of the split.
custom_rules	MlDetectionRule[]	An array of custom rule objects, which enable you to customize the way detectors operate. For example, a rule may dictate to the detector conditions under which results should be skipped. Kibana refers to custom rules as job rules.
detector_description	string	A description of the detector.
detector_index	integer	A unique identifier for the detector. This identifier is based on the order of the detectors in the analysis_config, starting at zero.
exclude_frequent	MlExcludeFrequent	Contains one of the following values: all, none, by, or over. If set, frequent entities are excluded from influencing the anomaly results. Entities can be considered frequent over time or frequent in a population. If you are working with both over and by fields, then you can set exclude_frequent to all for both fields, or to by or over for those specific fields.
field_name	Field	The field that the detector uses in the function. If you use an event rate function such as count or rare, do not specify this field.
function	string	The analysis function that is used. For example, count, rare, mean, min, max, and sum.
over_field_name	Field	The field used to split the data. In particular, this property is used for analyzing the splits with respect to the history of all splits. It is used for finding unusual values in the population of all splits.
partition_field_name	Field	The field used to segment the analysis. When you use this property, you have completely independent baselines for each value of this field.
use_null	boolean	Defines whether a new series is used as the null series when there is no value for the by or partition fields.