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.TFIMetricDataPoint

Description

Documentation

data TFIMetricDataPoint Source #

The performance metrics data points for Transaction Fraud Insights (TFI) model.

See: newTFIMetricDataPoint smart constructor.

Constructors

TFIMetricDataPoint'

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 TFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint Methods parseJSON :: Value -> Parser TFIMetricDataPoint # parseJSONList :: Value -> Parser [TFIMetricDataPoint] #
Generic TFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint Associated Types type Rep TFIMetricDataPoint :: Type -> Type # Methods from :: TFIMetricDataPoint -> Rep TFIMetricDataPoint x # to :: Rep TFIMetricDataPoint x -> TFIMetricDataPoint #
Read TFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint Methods readsPrec :: Int -> ReadS TFIMetricDataPoint # readList :: ReadS [TFIMetricDataPoint] # readPrec :: ReadPrec TFIMetricDataPoint # readListPrec :: ReadPrec [TFIMetricDataPoint] #
Show TFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint Methods showsPrec :: Int -> TFIMetricDataPoint -> ShowS # show :: TFIMetricDataPoint -> String # showList :: [TFIMetricDataPoint] -> ShowS #
NFData TFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint Methods rnf :: TFIMetricDataPoint -> () #
Eq TFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint Methods (==) :: TFIMetricDataPoint -> TFIMetricDataPoint -> Bool # (/=) :: TFIMetricDataPoint -> TFIMetricDataPoint -> Bool #
Hashable TFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint Methods hashWithSalt :: Int -> TFIMetricDataPoint -> Int # hash :: TFIMetricDataPoint -> Int #
type Rep TFIMetricDataPoint Source #
Instance details Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint type Rep TFIMetricDataPoint = D1 ('MetaData "TFIMetricDataPoint" "Amazonka.FraudDetector.Types.TFIMetricDataPoint" "amazonka-frauddetector-2.0-CdXFXtLV8DgKo4Kta7Jw61" 'False) (C1 ('MetaCons "TFIMetricDataPoint'" '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)))))

newTFIMetricDataPoint :: TFIMetricDataPoint Source #

Create a value of TFIMetricDataPoint 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:TFIMetricDataPoint', tFIMetricDataPoint_fpr - The false positive rate. This is the percentage of total legitimate events that are incorrectly predicted as fraud.

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

$sel:threshold:TFIMetricDataPoint', tFIMetricDataPoint_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:TFIMetricDataPoint', tFIMetricDataPoint_tpr - The true positive rate. This is the percentage of total fraud the model detects. Also known as capture rate.

tFIMetricDataPoint_fpr :: Lens' TFIMetricDataPoint (Maybe Double) Source #

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

tFIMetricDataPoint_precision :: Lens' TFIMetricDataPoint (Maybe Double) Source #

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

tFIMetricDataPoint_threshold :: Lens' TFIMetricDataPoint (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.

tFIMetricDataPoint_tpr :: Lens' TFIMetricDataPoint (Maybe Double) Source #

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