Amazonka.FraudDetector.Types.TFIMetricDataPoint

Documentation

data TFIMetricDataPoint

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

FromJSON TFIMetricDataPoint

Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint

Methods

parseJSON :: Value -> Parser TFIMetricDataPoint

parseJSONList :: Value -> Parser [TFIMetricDataPoint]

Generic TFIMetricDataPoint

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

Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint

Methods

readsPrec :: Int -> ReadS TFIMetricDataPoint

readList :: ReadS [TFIMetricDataPoint]

readPrec :: ReadPrec TFIMetricDataPoint

readListPrec :: ReadPrec [TFIMetricDataPoint]

Show TFIMetricDataPoint

Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint

Methods

showsPrec :: Int -> TFIMetricDataPoint -> ShowS

show :: TFIMetricDataPoint -> String

showList :: [TFIMetricDataPoint] -> ShowS

NFData TFIMetricDataPoint

Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint

Methods

rnf :: TFIMetricDataPoint -> ()

Eq TFIMetricDataPoint

Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint

Methods

(==) :: TFIMetricDataPoint -> TFIMetricDataPoint -> Bool

(/=) :: TFIMetricDataPoint -> TFIMetricDataPoint -> Bool

Hashable TFIMetricDataPoint

Defined in Amazonka.FraudDetector.Types.TFIMetricDataPoint

Methods

hashWithSalt :: Int -> TFIMetricDataPoint -> Int

hash :: TFIMetricDataPoint -> Int

type Rep TFIMetricDataPoint

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

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)

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

tFIMetricDataPoint_precision :: Lens' TFIMetricDataPoint (Maybe Double)

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

tFIMetricDataPoint_threshold :: Lens' TFIMetricDataPoint (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.

tFIMetricDataPoint_tpr :: Lens' TFIMetricDataPoint (Maybe Double)

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