public static interface GetEventPredictionResponse.Builder extends FraudDetectorResponse.Builder, SdkPojo, CopyableBuilder<GetEventPredictionResponse.Builder,GetEventPredictionResponse>
build, responseMetadata, responseMetadatasdkHttpResponse, sdkHttpResponseequalsBySdkFields, sdkFieldscopyapplyMutation, buildGetEventPredictionResponse.Builder modelScores(Collection<ModelScores> modelScores)
The model scores. Amazon Fraud Detector generates model scores between 0 and 1000, where 0 is low fraud risk and 1000 is high fraud risk. Model scores are directly related to the false positive rate (FPR). For example, a score of 600 corresponds to an estimated 10% false positive rate whereas a score of 900 corresponds to an estimated 2% false positive rate.
modelScores - The model scores. Amazon Fraud Detector generates model scores between 0 and 1000, where 0 is low
fraud risk and 1000 is high fraud risk. Model scores are directly related to the false positive rate
(FPR). For example, a score of 600 corresponds to an estimated 10% false positive rate whereas a score
of 900 corresponds to an estimated 2% false positive rate.GetEventPredictionResponse.Builder modelScores(ModelScores... modelScores)
The model scores. Amazon Fraud Detector generates model scores between 0 and 1000, where 0 is low fraud risk and 1000 is high fraud risk. Model scores are directly related to the false positive rate (FPR). For example, a score of 600 corresponds to an estimated 10% false positive rate whereas a score of 900 corresponds to an estimated 2% false positive rate.
modelScores - The model scores. Amazon Fraud Detector generates model scores between 0 and 1000, where 0 is low
fraud risk and 1000 is high fraud risk. Model scores are directly related to the false positive rate
(FPR). For example, a score of 600 corresponds to an estimated 10% false positive rate whereas a score
of 900 corresponds to an estimated 2% false positive rate.GetEventPredictionResponse.Builder modelScores(Consumer<ModelScores.Builder>... modelScores)
The model scores. Amazon Fraud Detector generates model scores between 0 and 1000, where 0 is low fraud risk and 1000 is high fraud risk. Model scores are directly related to the false positive rate (FPR). For example, a score of 600 corresponds to an estimated 10% false positive rate whereas a score of 900 corresponds to an estimated 2% false positive rate.
This is a convenience method that creates an instance of theModelScores.Builder avoiding the need to create
one manually via ModelScores.builder().
When the Consumer completes,
SdkBuilder.build() is called immediately
and its result is passed to #modelScores(List.
modelScores - a consumer that will call methods on
ModelScores.Builder#modelScores(java.util.Collection) GetEventPredictionResponse.Builder ruleResults(Collection<RuleResult> ruleResults)
The results from the rules.
ruleResults - The results from the rules.GetEventPredictionResponse.Builder ruleResults(RuleResult... ruleResults)
The results from the rules.
ruleResults - The results from the rules.GetEventPredictionResponse.Builder ruleResults(Consumer<RuleResult.Builder>... ruleResults)
The results from the rules.
This is a convenience method that creates an instance of theRuleResult.Builder avoiding the need to create
one manually via RuleResult.builder().
When the Consumer completes,
SdkBuilder.build() is called immediately
and its result is passed to #ruleResults(List.
ruleResults - a consumer that will call methods on
RuleResult.Builder#ruleResults(java.util.Collection) GetEventPredictionResponse.Builder externalModelOutputs(Collection<ExternalModelOutputs> externalModelOutputs)
The model scores for Amazon SageMaker models.
externalModelOutputs - The model scores for Amazon SageMaker models.GetEventPredictionResponse.Builder externalModelOutputs(ExternalModelOutputs... externalModelOutputs)
The model scores for Amazon SageMaker models.
externalModelOutputs - The model scores for Amazon SageMaker models.GetEventPredictionResponse.Builder externalModelOutputs(Consumer<ExternalModelOutputs.Builder>... externalModelOutputs)
The model scores for Amazon SageMaker models.
This is a convenience method that creates an instance of theExternalModelOutputs.Builder avoiding the need to
create one manually via
ExternalModelOutputs.builder().
When the Consumer completes,
SdkBuilder.build() is called
immediately and its result is passed to #externalModelOutputs(List.
externalModelOutputs - a consumer that will call methods on
ExternalModelOutputs.Builder#externalModelOutputs(java.util.Collection) Copyright © 2022. All rights reserved.