Class Influencer
java.lang.Object
co.elastic.clients.elasticsearch.ml.Influencer
- All Implemented Interfaces:
JsonpSerializable
- See Also:
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Nested Class Summary
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Field Summary
Modifier and TypeFieldDescriptionstatic final JsonpDeserializer<Influencer>
Json deserializer forInfluencer
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Method Summary
Modifier and TypeMethodDescriptionfinal long
Required - The length of the bucket in seconds.final String
foo()
Additional influencer properties are added, depending on the fields being analyzed.final String
Required - The field name of the influencer.final String
Required - The entity that influenced, contributed to, or was to blame for the anomaly.final double
Required - A normalized score between 0-100, which is based on the probability of the influencer in this bucket aggregated across detectors.final double
Required - A normalized score between 0-100, which is based on the probability of the influencer aggregated across detectors.final boolean
Required - If true, this is an interim result.final String
jobId()
Required - Identifier for the anomaly detection job.static Influencer
final double
Required - The probability that the influencer has this behavior, in the range 0 to 1.final String
Required - Internal.void
serialize
(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) Serialize this object to JSON.protected void
serializeInternal
(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) protected static void
final Time
Required - The start time of the bucket for which these results were calculated.toString()
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Field Details
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_DESERIALIZER
Json deserializer forInfluencer
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Method Details
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of
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bucketSpan
public final long bucketSpan()Required - The length of the bucket in seconds. This value matches the bucket span that is specified in the job.API name:
bucket_span
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influencerScore
public final double influencerScore()Required - A normalized score between 0-100, which is based on the probability of the influencer in this bucket aggregated across detectors. Unlikeinitial_influencer_score
, this value is updated by a re-normalization process as new data is analyzed.API name:
influencer_score
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influencerFieldName
Required - The field name of the influencer.API name:
influencer_field_name
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influencerFieldValue
Required - The entity that influenced, contributed to, or was to blame for the anomaly.API name:
influencer_field_value
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initialInfluencerScore
public final double initialInfluencerScore()Required - 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.API name:
initial_influencer_score
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isInterim
public final boolean isInterim()Required - If true, this is an interim result. In other words, the results are calculated based on partial input data.API name:
is_interim
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jobId
Required - Identifier for the anomaly detection job.API name:
job_id
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probability
public final double probability()Required - 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 theinfluencer_score
is provided as a human-readable and friendly interpretation of this value.API name:
probability
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resultType
Required - Internal. This value is always set toinfluencer
.API name:
result_type
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timestamp
Required - The start time of the bucket for which these results were calculated.API name:
timestamp
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foo
Additional influencer properties are added, depending on the fields being analyzed. For example, if it’s analyzinguser_name
as an influencer, a fielduser_name
is added to the result document. This information enables you to filter the anomaly results more easily.API name:
foo
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serialize
Serialize this object to JSON.- Specified by:
serialize
in interfaceJsonpSerializable
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serializeInternal
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toString
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setupInfluencerDeserializer
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