MachineLearning / Client / get_evaluation
get_evaluation#
- MachineLearning.Client.get_evaluation(**kwargs)#
Returns an
Evaluation
that includes metadata as well as the current status of theEvaluation
.See also: AWS API Documentation
Request Syntax
response = client.get_evaluation( EvaluationId='string' )
- Parameters:
EvaluationId (string) –
[REQUIRED]
The ID of the
Evaluation
to retrieve. The evaluation of eachMLModel
is recorded and cataloged. The ID provides the means to access the information.- Return type:
dict
- Returns:
Response Syntax
{ 'EvaluationId': 'string', 'MLModelId': 'string', 'EvaluationDataSourceId': 'string', 'InputDataLocationS3': 'string', 'CreatedByIamUser': 'string', 'CreatedAt': datetime(2015, 1, 1), 'LastUpdatedAt': datetime(2015, 1, 1), 'Name': 'string', 'Status': 'PENDING'|'INPROGRESS'|'FAILED'|'COMPLETED'|'DELETED', 'PerformanceMetrics': { 'Properties': { 'string': 'string' } }, 'LogUri': 'string', 'Message': 'string', 'ComputeTime': 123, 'FinishedAt': datetime(2015, 1, 1), 'StartedAt': datetime(2015, 1, 1) }
Response Structure
(dict) –
Represents the output of a
GetEvaluation
operation and describes anEvaluation
.EvaluationId (string) –
The evaluation ID which is same as the
EvaluationId
in the request.MLModelId (string) –
The ID of the
MLModel
that was the focus of the evaluation.EvaluationDataSourceId (string) –
The
DataSource
used for this evaluation.InputDataLocationS3 (string) –
The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
CreatedByIamUser (string) –
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.
CreatedAt (datetime) –
The time that the
Evaluation
was created. The time is expressed in epoch time.LastUpdatedAt (datetime) –
The time of the most recent edit to the
Evaluation
. The time is expressed in epoch time.Name (string) –
A user-supplied name or description of the
Evaluation
.Status (string) –
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 anMLModel
.INPROGRESS
- The evaluation is underway.FAILED
- The request to evaluate anMLModel
did not run to completion. It is not usable.COMPLETED
- The evaluation process completed successfully.DELETED
- TheEvaluation
is marked as deleted. It is not usable.
PerformanceMetrics (dict) –
Measurements of how well the
MLModel
performed using observations referenced by theDataSource
. One of the following metric is returned based on the type of theMLModel
: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.
Properties (dict) –
(string) –
(string) –
LogUri (string) –
A link to the file that contains logs of the
CreateEvaluation
operation.Message (string) –
A description of the most recent details about evaluating the
MLModel
.ComputeTime (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 theEvaluation
is in theCOMPLETED
state.FinishedAt (datetime) –
The epoch time when Amazon Machine Learning marked the
Evaluation
asCOMPLETED
orFAILED
.FinishedAt
is only available when theEvaluation
is in theCOMPLETED
orFAILED
state.StartedAt (datetime) –
The epoch time when Amazon Machine Learning marked the
Evaluation
asINPROGRESS
.StartedAt
isn’t available if theEvaluation
is in thePENDING
state.
Exceptions
MachineLearning.Client.exceptions.InvalidInputException
MachineLearning.Client.exceptions.ResourceNotFoundException
MachineLearning.Client.exceptions.InternalServerException