Amazonka.MachineLearning.GetEvaluation

Returns an Evaluation that includes metadata as well as the current status of the Evaluation.

Creating a Request

data GetEvaluation

See: newGetEvaluation smart constructor.

Constructors

GetEvaluation'

Fields

• evaluationId :: Text

  The ID of the Evaluation to retrieve. The evaluation of each MLModel is recorded and cataloged. The ID provides the means to access the information.

Instances

ToJSON GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

toJSON :: GetEvaluation -> Value

toEncoding :: GetEvaluation -> Encoding

toJSONList :: [GetEvaluation] -> Value

toEncodingList :: [GetEvaluation] -> Encoding

ToHeaders GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

toHeaders :: GetEvaluation -> [Header]

ToPath GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

toPath :: GetEvaluation -> ByteString

ToQuery GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

toQuery :: GetEvaluation -> QueryString

AWSRequest GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Associated Types

type AWSResponse GetEvaluation

Methods

request :: (Service -> Service) -> GetEvaluation -> Request GetEvaluation

response :: MonadResource m => (ByteStringLazy -> IO ByteStringLazy) -> Service -> Proxy GetEvaluation -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse GetEvaluation)))

Generic GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Associated Types

type Rep GetEvaluation :: Type -> Type

Methods

from :: GetEvaluation -> Rep GetEvaluation x

to :: Rep GetEvaluation x -> GetEvaluation

Read GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

readsPrec :: Int -> ReadS GetEvaluation

readList :: ReadS [GetEvaluation]

readPrec :: ReadPrec GetEvaluation

readListPrec :: ReadPrec [GetEvaluation]

Show GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

showsPrec :: Int -> GetEvaluation -> ShowS

show :: GetEvaluation -> String

showList :: [GetEvaluation] -> ShowS

NFData GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

rnf :: GetEvaluation -> ()

Eq GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

(==) :: GetEvaluation -> GetEvaluation -> Bool

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

Hashable GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

hashWithSalt :: Int -> GetEvaluation -> Int

hash :: GetEvaluation -> Int

type AWSResponse GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

type AWSResponse GetEvaluation = GetEvaluationResponse

type Rep GetEvaluation

Defined in Amazonka.MachineLearning.GetEvaluation

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

newGetEvaluation

Arguments

:: Text

GetEvaluation

-> GetEvaluation

Create a value of GetEvaluation 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:

GetEvaluation, getEvaluation_evaluationId - The ID of the Evaluation to retrieve. The evaluation of each MLModel is recorded and cataloged. The ID provides the means to access the information.

Request Lenses

getEvaluation_evaluationId :: Lens' GetEvaluation Text

The ID of the Evaluation to retrieve. The evaluation of each MLModel is recorded and cataloged. The ID provides the means to access the information.

Destructuring the Response

data GetEvaluationResponse

Represents the output of a GetEvaluation operation and describes an Evaluation.

See: newGetEvaluationResponse smart constructor.

Constructors

GetEvaluationResponse'

Fields

• computeTime :: Maybe Integer

  The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.

• createdAt :: Maybe POSIX

  The time that the Evaluation was created. The time is expressed in epoch time.

• createdByIamUser :: Maybe Text

  The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

• evaluationDataSourceId :: Maybe Text

  The DataSource used for this evaluation.

• evaluationId :: Maybe Text

  The evaluation ID which is same as the EvaluationId in the request.

• finishedAt :: Maybe POSIX

  The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.

• inputDataLocationS3 :: Maybe Text

  The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

• lastUpdatedAt :: Maybe POSIX

  The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

• logUri :: Maybe Text

  A link to the file that contains logs of the CreateEvaluation operation.

• mLModelId :: Maybe Text

  The ID of the MLModel that was the focus of the evaluation.

• message :: Maybe Text

  A description of the most recent details about evaluating the MLModel.

• name :: Maybe Text

  A user-supplied name or description of the Evaluation.

• performanceMetrics :: Maybe PerformanceMetrics

  Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

  • BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
  • RegressionRMSE: A 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: A multiclass MLModel uses the F1 score technique to measure performance.

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

• startedAt :: Maybe POSIX

  The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.

• status :: Maybe EntityStatus

  The status of the evaluation. This element can have one of the following values:

  • PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
  • INPROGRESS - The evaluation is underway.
  • FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
  • COMPLETED - The evaluation process completed successfully.
  • DELETED - The Evaluation is marked as deleted. It is not usable.
• httpStatus :: Int

  The response's http status code.

Instances

Generic GetEvaluationResponse

Defined in Amazonka.MachineLearning.GetEvaluation

Associated Types

type Rep GetEvaluationResponse :: Type -> Type

Methods

from :: GetEvaluationResponse -> Rep GetEvaluationResponse x

to :: Rep GetEvaluationResponse x -> GetEvaluationResponse

Read GetEvaluationResponse

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

readsPrec :: Int -> ReadS GetEvaluationResponse

readList :: ReadS [GetEvaluationResponse]

readPrec :: ReadPrec GetEvaluationResponse

readListPrec :: ReadPrec [GetEvaluationResponse]

Show GetEvaluationResponse

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

showsPrec :: Int -> GetEvaluationResponse -> ShowS

show :: GetEvaluationResponse -> String

showList :: [GetEvaluationResponse] -> ShowS

NFData GetEvaluationResponse

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

rnf :: GetEvaluationResponse -> ()

Eq GetEvaluationResponse

Defined in Amazonka.MachineLearning.GetEvaluation

Methods

(==) :: GetEvaluationResponse -> GetEvaluationResponse -> Bool

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

type Rep GetEvaluationResponse

Defined in Amazonka.MachineLearning.GetEvaluation

type Rep GetEvaluationResponse = D1 ('MetaData "GetEvaluationResponse" "Amazonka.MachineLearning.GetEvaluation" "amazonka-ml-2.0-A3JLJ63WvmfHxGBBIqhdRA" 'False) (C1 ('MetaCons "GetEvaluationResponse'" 'PrefixI 'True) ((((S1 ('MetaSel ('Just "computeTime") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Integer)) :*: S1 ('MetaSel ('Just "createdAt") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe POSIX))) :*: (S1 ('MetaSel ('Just "createdByIamUser") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "evaluationDataSourceId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)))) :*: ((S1 ('MetaSel ('Just "evaluationId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "finishedAt") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe POSIX))) :*: (S1 ('MetaSel ('Just "inputDataLocationS3") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "lastUpdatedAt") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe POSIX))))) :*: (((S1 ('MetaSel ('Just "logUri") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "mLModelId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text))) :*: (S1 ('MetaSel ('Just "message") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "name") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)))) :*: ((S1 ('MetaSel ('Just "performanceMetrics") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe PerformanceMetrics)) :*: S1 ('MetaSel ('Just "startedAt") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe POSIX))) :*: (S1 ('MetaSel ('Just "status") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe EntityStatus)) :*: S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int))))))

newGetEvaluationResponse

Arguments

:: Int

$sel:httpStatus:GetEvaluationResponse'

-> GetEvaluationResponse

Create a value of GetEvaluationResponse 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:

GetEvaluationResponse, getEvaluationResponse_computeTime - The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.

GetEvaluationResponse, getEvaluationResponse_createdAt - The time that the Evaluation was created. The time is expressed in epoch time.

GetEvaluationResponse, getEvaluationResponse_createdByIamUser - The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

GetEvaluationResponse, getEvaluationResponse_evaluationDataSourceId - The DataSource used for this evaluation.

GetEvaluation, getEvaluationResponse_evaluationId - The evaluation ID which is same as the EvaluationId in the request.

GetEvaluationResponse, getEvaluationResponse_finishedAt - The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.

GetEvaluationResponse, getEvaluationResponse_inputDataLocationS3 - The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

GetEvaluationResponse, getEvaluationResponse_lastUpdatedAt - The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

$sel:logUri:GetEvaluationResponse', getEvaluationResponse_logUri - A link to the file that contains logs of the CreateEvaluation operation.

GetEvaluationResponse, getEvaluationResponse_mLModelId - The ID of the MLModel that was the focus of the evaluation.

GetEvaluationResponse, getEvaluationResponse_message - A description of the most recent details about evaluating the MLModel.

GetEvaluationResponse, getEvaluationResponse_name - A user-supplied name or description of the Evaluation.

GetEvaluationResponse, getEvaluationResponse_performanceMetrics - Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
• RegressionRMSE: A 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: A multiclass MLModel uses the F1 score technique to measure performance.

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

GetEvaluationResponse, getEvaluationResponse_startedAt - The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.

GetEvaluationResponse, getEvaluationResponse_status - The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

$sel:httpStatus:GetEvaluationResponse', getEvaluationResponse_httpStatus - The response's http status code.

Response Lenses

getEvaluationResponse_computeTime :: Lens' GetEvaluationResponse (Maybe Integer)

The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.

getEvaluationResponse_createdAt :: Lens' GetEvaluationResponse (Maybe UTCTime)

The time that the Evaluation was created. The time is expressed in epoch time.

getEvaluationResponse_createdByIamUser :: Lens' GetEvaluationResponse (Maybe Text)

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

getEvaluationResponse_evaluationDataSourceId :: Lens' GetEvaluationResponse (Maybe Text)

The DataSource used for this evaluation.

getEvaluationResponse_evaluationId :: Lens' GetEvaluationResponse (Maybe Text)

The evaluation ID which is same as the EvaluationId in the request.

getEvaluationResponse_finishedAt :: Lens' GetEvaluationResponse (Maybe UTCTime)

The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.

getEvaluationResponse_inputDataLocationS3 :: Lens' GetEvaluationResponse (Maybe Text)

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

getEvaluationResponse_lastUpdatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime)

The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

getEvaluationResponse_logUri :: Lens' GetEvaluationResponse (Maybe Text)

A link to the file that contains logs of the CreateEvaluation operation.

getEvaluationResponse_mLModelId :: Lens' GetEvaluationResponse (Maybe Text)

The ID of the MLModel that was the focus of the evaluation.

getEvaluationResponse_message :: Lens' GetEvaluationResponse (Maybe Text)

A description of the most recent details about evaluating the MLModel.

getEvaluationResponse_name :: Lens' GetEvaluationResponse (Maybe Text)

A user-supplied name or description of the Evaluation.

getEvaluationResponse_performanceMetrics :: Lens' GetEvaluationResponse (Maybe PerformanceMetrics)

Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
• RegressionRMSE: A 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: A multiclass MLModel uses the F1 score technique to measure performance.

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

getEvaluationResponse_startedAt :: Lens' GetEvaluationResponse (Maybe UTCTime)

The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.

getEvaluationResponse_status :: Lens' GetEvaluationResponse (Maybe EntityStatus)

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

getEvaluationResponse_httpStatus :: Lens' GetEvaluationResponse Int

The response's http status code.