Copyright	(c) 2013-2023 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	Safe-Inferred
Language	Haskell2010

Amazonka.FraudDetector.Types.OFIMetricDataPoint

Description

Documentation

data OFIMetricDataPoint Source #

The Online Fraud Insights (OFI) model performance metrics data points.

See: newOFIMetricDataPoint smart constructor.

Constructors

OFIMetricDataPoint'

Fields

fpr :: Maybe Double
The false positive rate. This is the percentage of total legitimate events that are incorrectly predicted as fraud.
precision :: Maybe Double
The percentage of fraud events correctly predicted as fraudulent as compared to all events predicted as fraudulent.
threshold :: Maybe Double
The model threshold that specifies an acceptable fraud capture rate. For example, a threshold of 500 means any model score 500 or above is labeled as fraud.
tpr :: Maybe Double
The true positive rate. This is the percentage of total fraud the model detects. Also known as capture rate.

Instances

Instances details

FromJSON OFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.OFIMetricDataPoint Methods parseJSON :: Value -> Parser OFIMetricDataPoint # parseJSONList :: Value -> Parser [OFIMetricDataPoint] #
Generic OFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.OFIMetricDataPoint Associated Types type Rep OFIMetricDataPoint :: Type -> Type # Methods from :: OFIMetricDataPoint -> Rep OFIMetricDataPoint x # to :: Rep OFIMetricDataPoint x -> OFIMetricDataPoint #
Read OFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.OFIMetricDataPoint Methods readsPrec :: Int -> ReadS OFIMetricDataPoint # readList :: ReadS [OFIMetricDataPoint] # readPrec :: ReadPrec OFIMetricDataPoint # readListPrec :: ReadPrec [OFIMetricDataPoint] #
Show OFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.OFIMetricDataPoint Methods showsPrec :: Int -> OFIMetricDataPoint -> ShowS # show :: OFIMetricDataPoint -> String # showList :: [OFIMetricDataPoint] -> ShowS #
NFData OFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.OFIMetricDataPoint Methods rnf :: OFIMetricDataPoint -> () #
Eq OFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.OFIMetricDataPoint Methods (==) :: OFIMetricDataPoint -> OFIMetricDataPoint -> Bool # (/=) :: OFIMetricDataPoint -> OFIMetricDataPoint -> Bool #
Hashable OFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.OFIMetricDataPoint Methods hashWithSalt :: Int -> OFIMetricDataPoint -> Int # hash :: OFIMetricDataPoint -> Int #
type Rep OFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.OFIMetricDataPoint type Rep OFIMetricDataPoint = D1 ('MetaData "OFIMetricDataPoint" "Amazonka.FraudDetector.Types.OFIMetricDataPoint" "amazonka-frauddetector-2.0-CdXFXtLV8DgKo4Kta7Jw61" 'False) (C1 ('MetaCons "OFIMetricDataPoint'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "fpr") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double)) :: S1 ('MetaSel ('Just "precision") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double))) :: (S1 ('MetaSel ('Just "threshold") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double)) :*: S1 ('MetaSel ('Just "tpr") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double)))))

newOFIMetricDataPoint :: OFIMetricDataPoint Source #

Create a value of OFIMetricDataPoint with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:fpr:OFIMetricDataPoint', oFIMetricDataPoint_fpr - The false positive rate. This is the percentage of total legitimate events that are incorrectly predicted as fraud.

$sel:precision:OFIMetricDataPoint', oFIMetricDataPoint_precision - The percentage of fraud events correctly predicted as fraudulent as compared to all events predicted as fraudulent.

$sel:threshold:OFIMetricDataPoint', oFIMetricDataPoint_threshold - The model threshold that specifies an acceptable fraud capture rate. For example, a threshold of 500 means any model score 500 or above is labeled as fraud.

$sel:tpr:OFIMetricDataPoint', oFIMetricDataPoint_tpr - The true positive rate. This is the percentage of total fraud the model detects. Also known as capture rate.

oFIMetricDataPoint_fpr :: Lens' OFIMetricDataPoint (Maybe Double) Source #

The false positive rate. This is the percentage of total legitimate events that are incorrectly predicted as fraud.

oFIMetricDataPoint_precision :: Lens' OFIMetricDataPoint (Maybe Double) Source #

The percentage of fraud events correctly predicted as fraudulent as compared to all events predicted as fraudulent.

oFIMetricDataPoint_threshold :: Lens' OFIMetricDataPoint (Maybe Double) Source #

The model threshold that specifies an acceptable fraud capture rate. For example, a threshold of 500 means any model score 500 or above is labeled as fraud.

oFIMetricDataPoint_tpr :: Lens' OFIMetricDataPoint (Maybe Double) Source #

The true positive rate. This is the percentage of total fraud the model detects. Also known as capture rate.