Class Detector
java.lang.Object
co.elastic.clients.elasticsearch.ml.Detector
- All Implemented Interfaces:
- JsonpSerializable
- See Also:
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Nested Class SummaryNested Classes
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Field SummaryFieldsModifier and TypeFieldDescriptionstatic final JsonpDeserializer<Detector>Json deserializer forDetector
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Method SummaryModifier and TypeMethodDescriptionfinal StringThe field used to split the data.final List<DetectionRule>Custom rules enable you to customize the way detectors operate.final StringA description of the detector.final IntegerA unique identifier for the detector.final ExcludeFrequentIf set, frequent entities are excluded from influencing the anomaly results.final StringThe field that the detector uses in the function.final Stringfunction()The analysis function that is used.static Detectorfinal StringThe field used to split the data.final StringThe field used to segment the analysis.voidserialize(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) Serialize this object to JSON.protected voidserializeInternal(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) protected static voidtoString()final BooleanuseNull()Defines whether a new series is used as the null series when there is no value for the by or partition fields.
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Field Details- 
_DESERIALIZERJson deserializer forDetector
 
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Method Details- 
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byFieldNameThe 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.API name: by_field_name
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customRulesCustom rules enable you to customize the way detectors operate. For example, a rule may dictate conditions under which results should be skipped. Kibana refers to custom rules as job rules.API name: custom_rules
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detectorDescriptionA description of the detector.API name: detector_description
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detectorIndexA unique identifier for the detector. This identifier is based on the order of the detectors in theanalysis_config, starting at zero. If you specify a value for this property, it is ignored.API name: detector_index
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excludeFrequentIf 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, you can setexclude_frequenttoallfor both fields, or tobyoroverfor those specific fields.API name: exclude_frequent
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fieldNameThe 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. Thefield_namecannot contain double quotes or backslashes.API name: field_name
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functionThe analysis function that is used. For example,count,rare,mean,min,max, orsum.API name: function
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overFieldNameThe 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.API name: over_field_name
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partitionFieldNameThe field used to segment the analysis. When you use this property, you have completely independent baselines for each value of this field.API name: partition_field_name
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useNullDefines whether a new series is used as the null series when there is no value for the by or partition fields.API name: use_null
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serializeSerialize this object to JSON.- Specified by:
- serializein interface- JsonpSerializable
 
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serializeInternal
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toString
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setupDetectorDeserializer
 
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