Copyright	(c) 2013-2021 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay <brendan.g.hay+amazonka@gmail.com>
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	None

Amazonka.Rekognition.Types.TestingDataResult

Description

Documentation

data TestingDataResult Source #

Sagemaker Groundtruth format manifest files for the input, output and validation datasets that are used and created during testing.

See: newTestingDataResult smart constructor.

Constructors

TestingDataResult'

Fields

input :: Maybe TestingData
The testing dataset that was supplied for training.
output :: Maybe TestingData
The subset of the dataset that was actually tested. Some images (assets) might not be tested due to file formatting and other issues.
validation :: Maybe ValidationData
The location of the data validation manifest. The data validation manifest is created for the test dataset during model training.

Instances

Instances details

Eq TestingDataResult Source #
Instance details Defined in Amazonka.Rekognition.Types.TestingDataResult Methods (==) :: TestingDataResult -> TestingDataResult -> Bool # (/=) :: TestingDataResult -> TestingDataResult -> Bool #
Read TestingDataResult Source #
Instance details Defined in Amazonka.Rekognition.Types.TestingDataResult Methods readsPrec :: Int -> ReadS TestingDataResult # readList :: ReadS [TestingDataResult] # readPrec :: ReadPrec TestingDataResult # readListPrec :: ReadPrec [TestingDataResult] #
Show TestingDataResult Source #
Instance details Defined in Amazonka.Rekognition.Types.TestingDataResult Methods showsPrec :: Int -> TestingDataResult -> ShowS # show :: TestingDataResult -> String # showList :: [TestingDataResult] -> ShowS #
Generic TestingDataResult Source #
Instance details Defined in Amazonka.Rekognition.Types.TestingDataResult Associated Types type Rep TestingDataResult :: Type -> Type # Methods from :: TestingDataResult -> Rep TestingDataResult x # to :: Rep TestingDataResult x -> TestingDataResult #
NFData TestingDataResult Source #
Instance details Defined in Amazonka.Rekognition.Types.TestingDataResult Methods rnf :: TestingDataResult -> () #
Hashable TestingDataResult Source #
Instance details Defined in Amazonka.Rekognition.Types.TestingDataResult Methods hashWithSalt :: Int -> TestingDataResult -> Int # hash :: TestingDataResult -> Int #
FromJSON TestingDataResult Source #
Instance details Defined in Amazonka.Rekognition.Types.TestingDataResult Methods parseJSON :: Value -> Parser TestingDataResult # parseJSONList :: Value -> Parser [TestingDataResult] #
type Rep TestingDataResult Source #
Instance details Defined in Amazonka.Rekognition.Types.TestingDataResult type Rep TestingDataResult = D1 ('MetaData "TestingDataResult" "Amazonka.Rekognition.Types.TestingDataResult" "libZSservicesZSamazonka-rekognitionZSamazonka-rekognition" 'False) (C1 ('MetaCons "TestingDataResult'" 'PrefixI 'True) (S1 ('MetaSel ('Just "input") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe TestingData)) :: (S1 ('MetaSel ('Just "output") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe TestingData)) :: S1 ('MetaSel ('Just "validation") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe ValidationData)))))

newTestingDataResult :: TestingDataResult Source #

Create a value of TestingDataResult 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:input:TestingDataResult', testingDataResult_input - The testing dataset that was supplied for training.

$sel:output:TestingDataResult', testingDataResult_output - The subset of the dataset that was actually tested. Some images (assets) might not be tested due to file formatting and other issues.

$sel:validation:TestingDataResult', testingDataResult_validation - The location of the data validation manifest. The data validation manifest is created for the test dataset during model training.

testingDataResult_input :: Lens' TestingDataResult (Maybe TestingData) Source #

The testing dataset that was supplied for training.

testingDataResult_output :: Lens' TestingDataResult (Maybe TestingData) Source #

The subset of the dataset that was actually tested. Some images (assets) might not be tested due to file formatting and other issues.

testingDataResult_validation :: Lens' TestingDataResult (Maybe ValidationData) Source #

The location of the data validation manifest. The data validation manifest is created for the test dataset during model training.