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.LookoutEquipment.CreateModel

Contents

Creating a Request
Request Lenses
Destructuring the Response
Response Lenses

Description

Creates an ML model for data inference.

A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred.

Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy.

Synopsis

data CreateModel = CreateModel' {
- dataPreProcessingConfiguration :: Maybe DataPreProcessingConfiguration
- datasetSchema :: Maybe DatasetSchema
- evaluationDataEndTime :: Maybe POSIX
- evaluationDataStartTime :: Maybe POSIX
- labelsInputConfiguration :: Maybe LabelsInputConfiguration
- offCondition :: Maybe Text
- roleArn :: Maybe Text
- serverSideKmsKeyId :: Maybe Text
- tags :: Maybe [Tag]
- trainingDataEndTime :: Maybe POSIX
- trainingDataStartTime :: Maybe POSIX
- modelName :: Text
- datasetName :: Text
- clientToken :: Text
}
newCreateModel :: Text -> Text -> Text -> CreateModel
createModel_dataPreProcessingConfiguration :: Lens' CreateModel (Maybe DataPreProcessingConfiguration)
createModel_datasetSchema :: Lens' CreateModel (Maybe DatasetSchema)
createModel_evaluationDataEndTime :: Lens' CreateModel (Maybe UTCTime)
createModel_evaluationDataStartTime :: Lens' CreateModel (Maybe UTCTime)
createModel_labelsInputConfiguration :: Lens' CreateModel (Maybe LabelsInputConfiguration)
createModel_offCondition :: Lens' CreateModel (Maybe Text)
createModel_roleArn :: Lens' CreateModel (Maybe Text)
createModel_serverSideKmsKeyId :: Lens' CreateModel (Maybe Text)
createModel_tags :: Lens' CreateModel (Maybe [Tag])
createModel_trainingDataEndTime :: Lens' CreateModel (Maybe UTCTime)
createModel_trainingDataStartTime :: Lens' CreateModel (Maybe UTCTime)
createModel_modelName :: Lens' CreateModel Text
createModel_datasetName :: Lens' CreateModel Text
createModel_clientToken :: Lens' CreateModel Text
data CreateModelResponse = CreateModelResponse' {
- modelArn :: Maybe Text
- status :: Maybe ModelStatus
- httpStatus :: Int
}
newCreateModelResponse :: Int -> CreateModelResponse
createModelResponse_modelArn :: Lens' CreateModelResponse (Maybe Text)
createModelResponse_status :: Lens' CreateModelResponse (Maybe ModelStatus)
createModelResponse_httpStatus :: Lens' CreateModelResponse Int

Creating a Request

data CreateModel Source #

See: newCreateModel smart constructor.

Constructors

CreateModel'

Fields

dataPreProcessingConfiguration :: Maybe DataPreProcessingConfiguration
The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.
When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H
datasetSchema :: Maybe DatasetSchema
The data schema for the ML model being created.
evaluationDataEndTime :: Maybe POSIX
Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the ML model.
evaluationDataStartTime :: Maybe POSIX
Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the ML model.
labelsInputConfiguration :: Maybe LabelsInputConfiguration
The input configuration for the labels being used for the ML model that's being created.
offCondition :: Maybe Text
Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.
roleArn :: Maybe Text
The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the ML model.
serverSideKmsKeyId :: Maybe Text
Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
tags :: Maybe [Tag]
Any tags associated with the ML model being created.
trainingDataEndTime :: Maybe POSIX
Indicates the time reference in the dataset that should be used to end the subset of training data for the ML model.
trainingDataStartTime :: Maybe POSIX
Indicates the time reference in the dataset that should be used to begin the subset of training data for the ML model.
modelName :: Text
The name for the ML model to be created.
datasetName :: Text
The name of the dataset for the ML model being created.
clientToken :: Text
A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Instances

Instances details

ToJSON CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods toJSON :: CreateModel -> Value # toEncoding :: CreateModel -> Encoding # toJSONList :: [CreateModel] -> Value # toEncodingList :: [CreateModel] -> Encoding #
ToHeaders CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods toHeaders :: CreateModel -> [Header] #
ToPath CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods toPath :: CreateModel -> ByteString #
ToQuery CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods toQuery :: CreateModel -> QueryString #
AWSRequest CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Associated Types type AWSResponse CreateModel # Methods request :: (Service -> Service) -> CreateModel -> Request CreateModel # response :: MonadResource m => (ByteStringLazy -> IO ByteStringLazy) -> Service -> Proxy CreateModel -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse CreateModel))) #
Generic CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Associated Types type Rep CreateModel :: Type -> Type # Methods from :: CreateModel -> Rep CreateModel x # to :: Rep CreateModel x -> CreateModel #
Read CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods readsPrec :: Int -> ReadS CreateModel # readList :: ReadS [CreateModel] # readPrec :: ReadPrec CreateModel # readListPrec :: ReadPrec [CreateModel] #
Show CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods showsPrec :: Int -> CreateModel -> ShowS # show :: CreateModel -> String # showList :: [CreateModel] -> ShowS #
NFData CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods rnf :: CreateModel -> () #
Eq CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods (==) :: CreateModel -> CreateModel -> Bool # (/=) :: CreateModel -> CreateModel -> Bool #
Hashable CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods hashWithSalt :: Int -> CreateModel -> Int # hash :: CreateModel -> Int #
type AWSResponse CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel type AWSResponse CreateModel = CreateModelResponse
type Rep CreateModel Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel type Rep CreateModel = D1 ('MetaData "CreateModel" "Amazonka.LookoutEquipment.CreateModel" "amazonka-lookoutequipment-2.0-FBtgEViQ46F6elHeNaa8oC" 'False) (C1 ('MetaCons "CreateModel'" 'PrefixI 'True) (((S1 ('MetaSel ('Just "dataPreProcessingConfiguration") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe DataPreProcessingConfiguration)) :: (S1 ('MetaSel ('Just "datasetSchema") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe DatasetSchema)) :: S1 ('MetaSel ('Just "evaluationDataEndTime") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe POSIX)))) :: ((S1 ('MetaSel ('Just "evaluationDataStartTime") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe POSIX)) :: S1 ('MetaSel ('Just "labelsInputConfiguration") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe LabelsInputConfiguration))) :: (S1 ('MetaSel ('Just "offCondition") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: S1 ('MetaSel ('Just "roleArn") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text))))) :: ((S1 ('MetaSel ('Just "serverSideKmsKeyId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "tags") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [Tag])) :: S1 ('MetaSel ('Just "trainingDataEndTime") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe POSIX)))) :: ((S1 ('MetaSel ('Just "trainingDataStartTime") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe POSIX)) :: S1 ('MetaSel ('Just "modelName") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text)) :: (S1 ('MetaSel ('Just "datasetName") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text) :*: S1 ('MetaSel ('Just "clientToken") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text))))))

newCreateModel Source #

Arguments

:: Text	`CreateModel`
-> Text	`CreateModel`
-> Text	`$sel:clientToken:CreateModel'`
-> CreateModel

Create a value of CreateModel 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:dataPreProcessingConfiguration:CreateModel', createModel_dataPreProcessingConfiguration - The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

$sel:datasetSchema:CreateModel', createModel_datasetSchema - The data schema for the ML model being created.

$sel:evaluationDataEndTime:CreateModel', createModel_evaluationDataEndTime - Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the ML model.

$sel:evaluationDataStartTime:CreateModel', createModel_evaluationDataStartTime - Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the ML model.

$sel:labelsInputConfiguration:CreateModel', createModel_labelsInputConfiguration - The input configuration for the labels being used for the ML model that's being created.

$sel:offCondition:CreateModel', createModel_offCondition - Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.

$sel:roleArn:CreateModel', createModel_roleArn - The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the ML model.

$sel:serverSideKmsKeyId:CreateModel', createModel_serverSideKmsKeyId - Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.

$sel:tags:CreateModel', createModel_tags - Any tags associated with the ML model being created.

$sel:trainingDataEndTime:CreateModel', createModel_trainingDataEndTime - Indicates the time reference in the dataset that should be used to end the subset of training data for the ML model.

$sel:trainingDataStartTime:CreateModel', createModel_trainingDataStartTime - Indicates the time reference in the dataset that should be used to begin the subset of training data for the ML model.

CreateModel, createModel_modelName - The name for the ML model to be created.

CreateModel, createModel_datasetName - The name of the dataset for the ML model being created.

$sel:clientToken:CreateModel', createModel_clientToken - A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Request Lenses

createModel_dataPreProcessingConfiguration :: Lens' CreateModel (Maybe DataPreProcessingConfiguration) Source #

The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

createModel_datasetSchema :: Lens' CreateModel (Maybe DatasetSchema) Source #

The data schema for the ML model being created.

createModel_evaluationDataEndTime :: Lens' CreateModel (Maybe UTCTime) Source #

Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the ML model.

createModel_evaluationDataStartTime :: Lens' CreateModel (Maybe UTCTime) Source #

Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the ML model.

createModel_labelsInputConfiguration :: Lens' CreateModel (Maybe LabelsInputConfiguration) Source #

The input configuration for the labels being used for the ML model that's being created.

createModel_offCondition :: Lens' CreateModel (Maybe Text) Source #

Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.

createModel_roleArn :: Lens' CreateModel (Maybe Text) Source #

The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the ML model.

createModel_serverSideKmsKeyId :: Lens' CreateModel (Maybe Text) Source #

Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.

createModel_tags :: Lens' CreateModel (Maybe [Tag]) Source #

Any tags associated with the ML model being created.

createModel_trainingDataEndTime :: Lens' CreateModel (Maybe UTCTime) Source #

Indicates the time reference in the dataset that should be used to end the subset of training data for the ML model.

createModel_trainingDataStartTime :: Lens' CreateModel (Maybe UTCTime) Source #

Indicates the time reference in the dataset that should be used to begin the subset of training data for the ML model.

createModel_modelName :: Lens' CreateModel Text Source #

The name for the ML model to be created.

createModel_datasetName :: Lens' CreateModel Text Source #

The name of the dataset for the ML model being created.

createModel_clientToken :: Lens' CreateModel Text Source #

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Destructuring the Response

data CreateModelResponse Source #

See: newCreateModelResponse smart constructor.

Constructors

CreateModelResponse'
Fields modelArn :: Maybe Text The Amazon Resource Name (ARN) of the model being created. status :: Maybe ModelStatus Indicates the status of the `CreateModel` operation. httpStatus :: Int The response's http status code.

Instances

Instances details

Generic CreateModelResponse Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Associated Types type Rep CreateModelResponse :: Type -> Type # Methods from :: CreateModelResponse -> Rep CreateModelResponse x # to :: Rep CreateModelResponse x -> CreateModelResponse #
Read CreateModelResponse Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods readsPrec :: Int -> ReadS CreateModelResponse # readList :: ReadS [CreateModelResponse] # readPrec :: ReadPrec CreateModelResponse # readListPrec :: ReadPrec [CreateModelResponse] #
Show CreateModelResponse Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods showsPrec :: Int -> CreateModelResponse -> ShowS # show :: CreateModelResponse -> String # showList :: [CreateModelResponse] -> ShowS #
NFData CreateModelResponse Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods rnf :: CreateModelResponse -> () #
Eq CreateModelResponse Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel Methods (==) :: CreateModelResponse -> CreateModelResponse -> Bool # (/=) :: CreateModelResponse -> CreateModelResponse -> Bool #
type Rep CreateModelResponse Source #
Instance details Defined in Amazonka.LookoutEquipment.CreateModel type Rep CreateModelResponse = D1 ('MetaData "CreateModelResponse" "Amazonka.LookoutEquipment.CreateModel" "amazonka-lookoutequipment-2.0-FBtgEViQ46F6elHeNaa8oC" 'False) (C1 ('MetaCons "CreateModelResponse'" 'PrefixI 'True) (S1 ('MetaSel ('Just "modelArn") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "status") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe ModelStatus)) :: S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int))))

newCreateModelResponse Source #

Arguments

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

Create a value of CreateModelResponse 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:

CreateModelResponse, createModelResponse_modelArn - The Amazon Resource Name (ARN) of the model being created.

CreateModelResponse, createModelResponse_status - Indicates the status of the CreateModel operation.

$sel:httpStatus:CreateModelResponse', createModelResponse_httpStatus - The response's http status code.

Response Lenses

createModelResponse_modelArn :: Lens' CreateModelResponse (Maybe Text) Source #

The Amazon Resource Name (ARN) of the model being created.

createModelResponse_status :: Lens' CreateModelResponse (Maybe ModelStatus) Source #

Indicates the status of the CreateModel operation.

createModelResponse_httpStatus :: Lens' CreateModelResponse Int Source #

The response's http status code.