Amazonka.FraudDetector.Types.MetricDataPoint

Documentation

data MetricDataPoint

Model performance metrics data points.

See: newMetricDataPoint smart constructor.

Constructors

MetricDataPoint'

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 MetricDataPoint

Defined in Amazonka.FraudDetector.Types.MetricDataPoint

Methods

parseJSON :: Value -> Parser MetricDataPoint

parseJSONList :: Value -> Parser [MetricDataPoint]

Generic MetricDataPoint

Defined in Amazonka.FraudDetector.Types.MetricDataPoint

Associated Types

type Rep MetricDataPoint :: Type -> Type

Methods

from :: MetricDataPoint -> Rep MetricDataPoint x

to :: Rep MetricDataPoint x -> MetricDataPoint

Read MetricDataPoint

Defined in Amazonka.FraudDetector.Types.MetricDataPoint

Methods

readsPrec :: Int -> ReadS MetricDataPoint

readList :: ReadS [MetricDataPoint]

readPrec :: ReadPrec MetricDataPoint

readListPrec :: ReadPrec [MetricDataPoint]

Show MetricDataPoint

Defined in Amazonka.FraudDetector.Types.MetricDataPoint

Methods

showsPrec :: Int -> MetricDataPoint -> ShowS

show :: MetricDataPoint -> String

showList :: [MetricDataPoint] -> ShowS

NFData MetricDataPoint

Defined in Amazonka.FraudDetector.Types.MetricDataPoint

Methods

rnf :: MetricDataPoint -> ()

Eq MetricDataPoint

Defined in Amazonka.FraudDetector.Types.MetricDataPoint

Methods

(==) :: MetricDataPoint -> MetricDataPoint -> Bool

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

Hashable MetricDataPoint

Defined in Amazonka.FraudDetector.Types.MetricDataPoint

Methods

hashWithSalt :: Int -> MetricDataPoint -> Int

hash :: MetricDataPoint -> Int

type Rep MetricDataPoint

Defined in Amazonka.FraudDetector.Types.MetricDataPoint

type Rep MetricDataPoint = D1 ('MetaData "MetricDataPoint" "Amazonka.FraudDetector.Types.MetricDataPoint" "amazonka-frauddetector-2.0-CdXFXtLV8DgKo4Kta7Jw61" 'False) (C1 ('MetaCons "MetricDataPoint'" '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)))))

newMetricDataPoint :: MetricDataPoint

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

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

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

metricDataPoint_fpr :: Lens' MetricDataPoint (Maybe Double)

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

metricDataPoint_precision :: Lens' MetricDataPoint (Maybe Double)

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

metricDataPoint_threshold :: Lens' MetricDataPoint (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.

metricDataPoint_tpr :: Lens' MetricDataPoint (Maybe Double)

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