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.MachineLearning.UpdateMLModel

Contents

Creating a Request
Request Lenses
Destructuring the Response
Response Lenses

Description

Updates the MLModelName and the ScoreThreshold of an MLModel.

You can use the GetMLModel operation to view the contents of the updated data element.

Creating a Request

data UpdateMLModel Source #

See: newUpdateMLModel smart constructor.

Constructors

UpdateMLModel'

Fields

mLModelName :: Maybe Text
A user-supplied name or description of the MLModel.
scoreThreshold :: Maybe Double
The ScoreThreshold used in binary classification MLModel that marks the boundary between a positive prediction and a negative prediction.
Output values greater than or equal to the ScoreThreshold receive a positive result from the MLModel, such as true. Output values less than the ScoreThreshold receive a negative response from the MLModel, such as false.
mLModelId :: Text
The ID assigned to the MLModel during creation.

Instances

Instances details

ToJSON UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods toJSON :: UpdateMLModel -> Value # toEncoding :: UpdateMLModel -> Encoding # toJSONList :: [UpdateMLModel] -> Value # toEncodingList :: [UpdateMLModel] -> Encoding #
ToHeaders UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods toHeaders :: UpdateMLModel -> [Header] #
ToPath UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods toPath :: UpdateMLModel -> ByteString #
ToQuery UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods toQuery :: UpdateMLModel -> QueryString #
AWSRequest UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Associated Types type AWSResponse UpdateMLModel # Methods request :: (Service -> Service) -> UpdateMLModel -> Request UpdateMLModel # response :: MonadResource m => (ByteStringLazy -> IO ByteStringLazy) -> Service -> Proxy UpdateMLModel -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse UpdateMLModel))) #
Generic UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Associated Types type Rep UpdateMLModel :: Type -> Type # Methods from :: UpdateMLModel -> Rep UpdateMLModel x # to :: Rep UpdateMLModel x -> UpdateMLModel #
Read UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods readsPrec :: Int -> ReadS UpdateMLModel # readList :: ReadS [UpdateMLModel] # readPrec :: ReadPrec UpdateMLModel # readListPrec :: ReadPrec [UpdateMLModel] #
Show UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods showsPrec :: Int -> UpdateMLModel -> ShowS # show :: UpdateMLModel -> String # showList :: [UpdateMLModel] -> ShowS #
NFData UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods rnf :: UpdateMLModel -> () #
Eq UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods (==) :: UpdateMLModel -> UpdateMLModel -> Bool # (/=) :: UpdateMLModel -> UpdateMLModel -> Bool #
Hashable UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods hashWithSalt :: Int -> UpdateMLModel -> Int # hash :: UpdateMLModel -> Int #
type AWSResponse UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel type AWSResponse UpdateMLModel = UpdateMLModelResponse
type Rep UpdateMLModel Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel type Rep UpdateMLModel = D1 ('MetaData "UpdateMLModel" "Amazonka.MachineLearning.UpdateMLModel" "amazonka-ml-2.0-A3JLJ63WvmfHxGBBIqhdRA" 'False) (C1 ('MetaCons "UpdateMLModel'" 'PrefixI 'True) (S1 ('MetaSel ('Just "mLModelName") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "scoreThreshold") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double)) :: S1 ('MetaSel ('Just "mLModelId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text))))

newUpdateMLModel Source #

Arguments

:: Text	`UpdateMLModel`
-> UpdateMLModel

Create a value of UpdateMLModel 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:mLModelName:UpdateMLModel', updateMLModel_mLModelName - A user-supplied name or description of the MLModel.

UpdateMLModel, updateMLModel_scoreThreshold - The ScoreThreshold used in binary classification MLModel that marks the boundary between a positive prediction and a negative prediction.

Output values greater than or equal to the ScoreThreshold receive a positive result from the MLModel, such as true. Output values less than the ScoreThreshold receive a negative response from the MLModel, such as false.

UpdateMLModel, updateMLModel_mLModelId - The ID assigned to the MLModel during creation.

Request Lenses

updateMLModel_mLModelName :: Lens' UpdateMLModel (Maybe Text) Source #

A user-supplied name or description of the MLModel.

updateMLModel_scoreThreshold :: Lens' UpdateMLModel (Maybe Double) Source #

The ScoreThreshold used in binary classification MLModel that marks the boundary between a positive prediction and a negative prediction.

Output values greater than or equal to the ScoreThreshold receive a positive result from the MLModel, such as true. Output values less than the ScoreThreshold receive a negative response from the MLModel, such as false.

updateMLModel_mLModelId :: Lens' UpdateMLModel Text Source #

The ID assigned to the MLModel during creation.

Destructuring the Response

data UpdateMLModelResponse Source #

Represents the output of an UpdateMLModel operation.

You can see the updated content by using the GetMLModel operation.

See: newUpdateMLModelResponse smart constructor.

Constructors

UpdateMLModelResponse'
Fields mLModelId :: Maybe Text The ID assigned to the `MLModel` during creation. This value should be identical to the value of the `MLModelID` in the request. httpStatus :: Int The response's http status code.

Instances

Instances details

Generic UpdateMLModelResponse Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Associated Types type Rep UpdateMLModelResponse :: Type -> Type # Methods from :: UpdateMLModelResponse -> Rep UpdateMLModelResponse x # to :: Rep UpdateMLModelResponse x -> UpdateMLModelResponse #
Read UpdateMLModelResponse Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods readsPrec :: Int -> ReadS UpdateMLModelResponse # readList :: ReadS [UpdateMLModelResponse] # readPrec :: ReadPrec UpdateMLModelResponse # readListPrec :: ReadPrec [UpdateMLModelResponse] #
Show UpdateMLModelResponse Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods showsPrec :: Int -> UpdateMLModelResponse -> ShowS # show :: UpdateMLModelResponse -> String # showList :: [UpdateMLModelResponse] -> ShowS #
NFData UpdateMLModelResponse Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods rnf :: UpdateMLModelResponse -> () #
Eq UpdateMLModelResponse Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel Methods (==) :: UpdateMLModelResponse -> UpdateMLModelResponse -> Bool # (/=) :: UpdateMLModelResponse -> UpdateMLModelResponse -> Bool #
type Rep UpdateMLModelResponse Source #
Instance details Defined in Amazonka.MachineLearning.UpdateMLModel type Rep UpdateMLModelResponse = D1 ('MetaData "UpdateMLModelResponse" "Amazonka.MachineLearning.UpdateMLModel" "amazonka-ml-2.0-A3JLJ63WvmfHxGBBIqhdRA" 'False) (C1 ('MetaCons "UpdateMLModelResponse'" 'PrefixI 'True) (S1 ('MetaSel ('Just "mLModelId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int)))

newUpdateMLModelResponse Source #

Arguments

:: Int	`$sel:httpStatus:UpdateMLModelResponse'`
-> UpdateMLModelResponse

Create a value of UpdateMLModelResponse 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:

UpdateMLModel, updateMLModelResponse_mLModelId - The ID assigned to the MLModel during creation. This value should be identical to the value of the MLModelID in the request.

$sel:httpStatus:UpdateMLModelResponse', updateMLModelResponse_httpStatus - The response's http status code.

Response Lenses

updateMLModelResponse_mLModelId :: Lens' UpdateMLModelResponse (Maybe Text) Source #

The ID assigned to the MLModel during creation. This value should be identical to the value of the MLModelID in the request.

updateMLModelResponse_httpStatus :: Lens' UpdateMLModelResponse Int Source #

The response's http status code.