Skip to content

GetEventPredictionResult

Source code in docs_src/capo_frauddetector/types/get_event_prediction_result.py 
13
14
15
16
17
18
19
20
21
22
23
24
25
class GetEventPredictionResult(TypedDict, closed=True):
    model_scores: NotRequired[
        "capo_frauddetector.types.list_of_model_scores.ListOfModelScores"
    ]
    """<p>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.</p>"""
    rule_results: NotRequired[
        "capo_frauddetector.types.list_of_rule_results.ListOfRuleResults"
    ]
    """<p>The results from the rules.</p>"""
    external_model_outputs: NotRequired[
        "capo_frauddetector.types.list_of_external_model_outputs.ListOfExternalModelOutputs"
    ]
    """<p>The model scores for Amazon SageMaker models.</p>"""

external_model_outputs instance-attribute 

external_model_outputs: NotRequired[ListOfExternalModelOutputs]

The model scores for Amazon SageMaker models.

model_scores instance-attribute 

model_scores: NotRequired[ListOfModelScores]

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.

rule_results instance-attribute 

rule_results: NotRequired[ListOfRuleResults]

The results from the rules.