GetEvaluation
Returns an Evaluation that includes metadata as well as the current status of the Evaluation.
Request Syntax
{
   "EvaluationId": "string"
}
    
      Request Parameters
For information about the parameters that are common to all actions, see Common Parameters.
The request accepts the following data in JSON format.
- EvaluationId
 - 
               
The ID of the
Evaluationto retrieve. The evaluation of eachMLModelis recorded and cataloged. The ID provides the means to access the information.Type: String
Length Constraints: Minimum length of 1. Maximum length of 64.
Pattern:
[a-zA-Z0-9_.-]+Required: Yes
 
Response Syntax
{
   "ComputeTime": number,
   "CreatedAt": number,
   "CreatedByIamUser": "string",
   "EvaluationDataSourceId": "string",
   "EvaluationId": "string",
   "FinishedAt": number,
   "InputDataLocationS3": "string",
   "LastUpdatedAt": number,
   "LogUri": "string",
   "Message": "string",
   "MLModelId": "string",
   "Name": "string",
   "PerformanceMetrics": { 
      "Properties": { 
         "string" : "string" 
      }
   },
   "StartedAt": number,
   "Status": "string"
}
    
      Response Elements
If the action is successful, the service sends back an HTTP 200 response.
The following data is returned in JSON format by the service.
- ComputeTime
 - 
               
The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the
Evaluation, normalized and scaled on computation resources.ComputeTimeis only available if theEvaluationis in theCOMPLETEDstate.Type: Long
 - CreatedAt
 - 
               
The time that the
Evaluationwas created. The time is expressed in epoch time.Type: Timestamp
 - 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)) - EvaluationDataSourceId
 - 
               
The
DataSourceused for this evaluation.Type: String
Length Constraints: Minimum length of 1. Maximum length of 64.
Pattern:
[a-zA-Z0-9_.-]+ - EvaluationId
 - 
               
The evaluation ID which is same as the
EvaluationIdin the request.Type: String
Length Constraints: Minimum length of 1. Maximum length of 64.
Pattern:
[a-zA-Z0-9_.-]+ - FinishedAt
 - 
               
The epoch time when Amazon Machine Learning marked the
EvaluationasCOMPLETEDorFAILED.FinishedAtis only available when theEvaluationis in theCOMPLETEDorFAILEDstate.Type: Timestamp
 - InputDataLocationS3
 - 
               
The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
Type: String
Length Constraints: Maximum length of 2048.
Pattern:
s3://([^/]+)(/.*)? - LastUpdatedAt
 - 
               
The time of the most recent edit to the
Evaluation. The time is expressed in epoch time.Type: Timestamp
 - LogUri
 - 
               
A link to the file that contains logs of the
CreateEvaluationoperation.Type: String
 - Message
 - 
               
A description of the most recent details about evaluating the
MLModel.Type: String
Length Constraints: Maximum length of 10240.
 - MLModelId
 - 
               
The ID of the
MLModelthat was the focus of the evaluation.Type: String
Length Constraints: Minimum length of 1. Maximum length of 64.
Pattern:
[a-zA-Z0-9_.-]+ - Name
 - 
               
A user-supplied name or description of the
Evaluation.Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$ - PerformanceMetrics
 - 
               
Measurements of how well the
MLModelperformed using observations referenced by theDataSource. One of the following metric is returned based on the type of theMLModel:- 
                     
BinaryAUC: A binary
MLModeluses the Area Under the Curve (AUC) technique to measure performance. - 
                     
RegressionRMSE: A regression
MLModeluses 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
MLModeluses the F1 score technique to measure performance. 
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
Type: PerformanceMetrics object
 - 
                     
 - StartedAt
 - 
               
The epoch time when Amazon Machine Learning marked the
EvaluationasINPROGRESS.StartedAtisn't available if theEvaluationis in thePENDINGstate.Type: Timestamp
 - 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 anMLModel. - 
                     
INPROGRESS- The evaluation is underway. - 
                     
FAILED- The request to evaluate anMLModeldid not run to completion. It is not usable. - 
                     
COMPLETED- The evaluation process completed successfully. - 
                     
DELETED- TheEvaluationis marked as deleted. It is not usable. 
Type: String
Valid Values:
PENDING | INPROGRESS | FAILED | COMPLETED | DELETED - 
                     
 
Errors
For information about the errors that are common to all actions, see Common Errors.
- InternalServerException
 - 
               
An error on the server occurred when trying to process a request.
HTTP Status Code: 500
 - InvalidInputException
 - 
               
An error on the client occurred. Typically, the cause is an invalid input value.
HTTP Status Code: 400
 - ResourceNotFoundException
 - 
               
A specified resource cannot be located.
HTTP Status Code: 400
 
Examples
The following is a sample request and response of the GetEvaluation operation.
This example illustrates one usage of GetEvaluation.
Sample Request
POST / HTTP/1.1
Host: machinelearning.<region>.<domain>
x-amz-Date: <Date>
Authorization: AWS4-HMAC-SHA256 Credential=<Credential>, SignedHeaders=contenttype;date;host;user-agent;x-amz-date;x-amz-target;x-amzn-requestid,Signature=<Signature>
User-Agent: <UserAgentString>
Content-Type: application/x-amz-json-1.1
Content-Length: <PayloadSizeBytes>
Connection: Keep-Alive
X-Amz-Target: AmazonML_20141212.GetEvaluation
{"EvaluationId": "ev-2014-09-12-15-14-04-924"}
          
          
            Sample Response
HTTP/1.1 200 OK
x-amzn-RequestId: <RequestId>
Content-Type: application/x-amz-json-1.1
Content-Length: <PayloadSizeBytes>
Date: <Date>
{
  "CreatedAt":1410560805.669,
  "CreatedByIamUser":"arn:aws:iam::<awsAccountId>:user/user",
  "EvaluationDataSourceId":"EXAMPLE-ev-ds-2014-09-12-15-14-04-411",
  "EvaluationId":"ev-2014-09-12-15-14-04-924",
  "InputDataLocationS3": "s3://eml-test-EXAMPLE/example.csv", 
  "LastUpdatedAt":1410560805.669,
  "LogUri": "https://s3bucket/locationToLogs/logname.tar.gz",
  "Name":"EXAMPLE",
  "PerformanceMetrics":{"Properties":{}},
  "MLModelId":"EXAMPLE-pr-2014-09-12-15-14-04-924",
  "Status":"COMPLETED",
  "ComputeTime":"185200",
  "FinishedAt":1410560805.669,
  "StartedAt":1410560805.669
}
          
       
    
      See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following: