The label schema.
Contents
- labelMapper
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The label mapper maps the Amazon Fraud Detector supported model classification labels (
FRAUD,LEGIT) to the appropriate event type labels. For example, if "FRAUD" and "LEGIT" are Amazon Fraud Detector supported labels, this mapper could be:{"FRAUD" => ["0"],"LEGIT" => ["1"]}or{"FRAUD" => ["false"],"LEGIT" => ["true"]}or{"FRAUD" => ["fraud", "abuse"],"LEGIT" => ["legit", "safe"]}. The value part of the mapper is a list, because you may have multiple label variants from your event type for a single Amazon Fraud Detector label.Type: String to array of strings map
Required: No
- unlabeledEventsTreatment
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The action to take for unlabeled events.
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Use
IGNOREif you want the unlabeled events to be ignored. This is recommended when the majority of the events in the dataset are labeled. -
Use
FRAUDif you want to categorize all unlabeled events as “Fraud”. This is recommended when most of the events in your dataset are fraudulent. -
Use
LEGITif you want to categorize all unlabeled events as “Legit”. This is recommended when most of the events in your dataset are legitimate. -
Use
AUTOif you want Amazon Fraud Detector to decide how to use the unlabeled data. This is recommended when there is significant unlabeled events in the dataset.
By default, Amazon Fraud Detector ignores the unlabeled data.
Type: String
Valid Values:
IGNORE | FRAUD | LEGIT | AUTORequired: No
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See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following:
