Evaluation
Represents the output of GetEvaluation
operation.
The content consists of the detailed metadata and data file information and the current status of the
Evaluation
.
Contents
- ComputeTime
-
Long integer type that is a 64-bit signed number.
Type: Long
Required: No
- CreatedAt
-
The time that the
Evaluation
was created. The time is expressed in epoch time.Type: Timestamp
Required: No
- 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.
Type: String
Pattern:
arn:aws:iam::[0-9]+:((user/.+)|(root))
Required: No
- EvaluationDataSourceId
-
The ID of the
DataSource
that is used to evaluate theMLModel
.Type: String
Length Constraints: Minimum length of 1. Maximum length of 64.
Pattern:
[a-zA-Z0-9_.-]+
Required: No
- EvaluationId
-
The ID that is assigned to the
Evaluation
at creation.Type: String
Length Constraints: Minimum length of 1. Maximum length of 64.
Pattern:
[a-zA-Z0-9_.-]+
Required: No
- FinishedAt
-
A timestamp represented in epoch time.
Type: Timestamp
Required: No
- InputDataLocationS3
-
The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
Type: String
Length Constraints: Maximum length of 2048.
Pattern:
s3://([^/]+)(/.*)?
Required: No
- LastUpdatedAt
-
The time of the most recent edit to the
Evaluation
. The time is expressed in epoch time.Type: Timestamp
Required: No
- Message
-
A description of the most recent details about evaluating the
MLModel
.Type: String
Length Constraints: Maximum length of 10240.
Required: No
- MLModelId
-
The ID of the
MLModel
that is the focus of the evaluation.Type: String
Length Constraints: Minimum length of 1. Maximum length of 64.
Pattern:
[a-zA-Z0-9_.-]+
Required: No
- Name
-
A user-supplied name or description of the
Evaluation
.Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$
Required: No
- PerformanceMetrics
-
Measurements of how well the
MLModel
performed, using observations referenced by theDataSource
. One of the following metrics 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.
Type: PerformanceMetrics object
Required: No
-
- StartedAt
-
A timestamp represented in epoch time.
Type: Timestamp
Required: No
- Status
-
The status of the evaluation. This element can have one of the following values:
-
PENDING
- Amazon Machine Learning (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.
Type: String
Valid Values:
PENDING | INPROGRESS | FAILED | COMPLETED | DELETED
Required: No
-
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following: