Amazonka.MachineLearning.Types.PerformanceMetrics

Documentation

data PerformanceMetrics

Measurements of how well the MLModel performed on known observations. One of the following metrics is returned, based on the type of the MLModel:

• BinaryAUC: The binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
• RegressionRMSE: The regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.
• MulticlassAvgFScore: The multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

See: newPerformanceMetrics smart constructor.

Constructors

PerformanceMetrics'

Fields

• properties :: Maybe (HashMap Text Text)

Instances

FromJSON PerformanceMetrics

Defined in Amazonka.MachineLearning.Types.PerformanceMetrics

Methods

parseJSON :: Value -> Parser PerformanceMetrics

parseJSONList :: Value -> Parser [PerformanceMetrics]

Generic PerformanceMetrics

Defined in Amazonka.MachineLearning.Types.PerformanceMetrics

Associated Types

type Rep PerformanceMetrics :: Type -> Type

Methods

from :: PerformanceMetrics -> Rep PerformanceMetrics x

to :: Rep PerformanceMetrics x -> PerformanceMetrics

Read PerformanceMetrics

Defined in Amazonka.MachineLearning.Types.PerformanceMetrics

Methods

readsPrec :: Int -> ReadS PerformanceMetrics

readList :: ReadS [PerformanceMetrics]

readPrec :: ReadPrec PerformanceMetrics

readListPrec :: ReadPrec [PerformanceMetrics]

Show PerformanceMetrics

Defined in Amazonka.MachineLearning.Types.PerformanceMetrics

Methods

showsPrec :: Int -> PerformanceMetrics -> ShowS

show :: PerformanceMetrics -> String

showList :: [PerformanceMetrics] -> ShowS

NFData PerformanceMetrics

Defined in Amazonka.MachineLearning.Types.PerformanceMetrics

Methods

rnf :: PerformanceMetrics -> ()

Eq PerformanceMetrics

Defined in Amazonka.MachineLearning.Types.PerformanceMetrics

Methods

(==) :: PerformanceMetrics -> PerformanceMetrics -> Bool

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

Hashable PerformanceMetrics

Defined in Amazonka.MachineLearning.Types.PerformanceMetrics

Methods

hashWithSalt :: Int -> PerformanceMetrics -> Int

hash :: PerformanceMetrics -> Int

type Rep PerformanceMetrics

Defined in Amazonka.MachineLearning.Types.PerformanceMetrics

type Rep PerformanceMetrics = D1 ('MetaData "PerformanceMetrics" "Amazonka.MachineLearning.Types.PerformanceMetrics" "amazonka-ml-2.0-A3JLJ63WvmfHxGBBIqhdRA" 'False) (C1 ('MetaCons "PerformanceMetrics'" 'PrefixI 'True) (S1 ('MetaSel ('Just "properties") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe (HashMap Text Text)))))

newPerformanceMetrics :: PerformanceMetrics

Create a value of PerformanceMetrics 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:properties:PerformanceMetrics', performanceMetrics_properties - Undocumented member.

performanceMetrics_properties :: Lens' PerformanceMetrics (Maybe (HashMap Text Text))

Undocumented member.