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

MlAnalysisConfigRead [interface-MlAnalysisConfigRead]

Name	Type	Description
bucket_span	Duration	The size of the interval that the analysis is aggregated into, typically between 5m and 1h.
categorization_analyzer	MlCategorizationAnalyzer	If categorization_field_name is specified, you can also define the analyzer that is used to interpret the categorization field. This property cannot be used at the same time as categorization_filters. The categorization analyzer specifies how the categorization_field is interpreted by the categorization process.
categorization_field_name	Field	If this property is specified, the values of the specified field will be categorized. The resulting categories must be used in a detector by setting by_field_name, over_field_name, or partition_field_name to the keyword mlcategory.
categorization_filters	string[]	If categorization_field_name is specified, you can also define optional filters. This property expects an array of regular expressions. The expressions are used to filter out matching sequences from the categorization field values.
detectors	MlDetectorRead[]	An array of detector configuration objects. Detector configuration objects specify which data fields a job analyzes. They also specify which analytical functions are used. You can specify multiple detectors for a job.
influencers	Field[]	A comma separated list of influencer field names. Typically these can be the by, over, or partition fields that are used in the detector configuration. You might also want to use a field name that is not specifically named in a detector, but is available as part of the input data. When you use multiple detectors, the use of influencers is recommended as it aggregates results for each influencer entity.
latency	Duration	The size of the window in which to expect data that is out of time order. Defaults to no latency. If you specify a non-zero value, it must be greater than or equal to one second.
model_prune_window	Duration	Advanced configuration option. Affects the pruning of models that have not been updated for the given time duration. The value must be set to a multiple of the bucket_span. If set too low, important information may be removed from the model. Typically, set to 30d or longer. If not set, model pruning only occurs if the model memory status reaches the soft limit or the hard limit. For jobs created in 8.1 and later, the default value is the greater of 30d or 20 times bucket_span.
multivariate_by_fields	boolean	This functionality is reserved for internal use. It is not supported for use in customer environments and is not subject to the support SLA of official GA features. If set to true, the analysis will automatically find correlations between metrics for a given by field value and report anomalies when those correlations cease to hold.
per_partition_categorization	MlPerPartitionCategorization	Settings related to how categorization interacts with partition fields.
summary_count_field_name	Field	If this property is specified, the data that is fed to the job is expected to be pre-summarized. This property value is the name of the field that contains the count of raw data points that have been summarized. The same summary_count_field_name applies to all detectors in the job.