MachineLearning / Client / describe_evaluations

describe_evaluations#

MachineLearning.Client.describe_evaluations(**kwargs)#

Returns a list of DescribeEvaluations that match the search criteria in the request.

Request Syntax

response = client.describe_evaluations(
    FilterVariable='CreatedAt'|'LastUpdatedAt'|'Status'|'Name'|'IAMUser'|'MLModelId'|'DataSourceId'|'DataURI',
    EQ='string',
    GT='string',
    LT='string',
    GE='string',
    LE='string',
    NE='string',
    Prefix='string',
    SortOrder='asc'|'dsc',
    NextToken='string',
    Limit=123
)

Parameters:

FilterVariable (string) –
Use one of the following variable to filter a list of Evaluation objects:
- CreatedAt - Sets the search criteria to the Evaluation creation date.
- Status - Sets the search criteria to the Evaluation status.
- Name - Sets the search criteria to the contents of Evaluation Name.
- IAMUser - Sets the search criteria to the user account that invoked an Evaluation.
- MLModelId - Sets the search criteria to the MLModel that was evaluated.
- DataSourceId - Sets the search criteria to the DataSource used in Evaluation.
- DataUri - Sets the search criteria to the data file(s) used in Evaluation. The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory.
EQ (string) – The equal to operator. The Evaluation results will have FilterVariable values that exactly match the value specified with EQ.
GT (string) – The greater than operator. The Evaluation results will have FilterVariable values that are greater than the value specified with GT.
LT (string) – The less than operator. The Evaluation results will have FilterVariable values that are less than the value specified with LT.
GE (string) – The greater than or equal to operator. The Evaluation results will have FilterVariable values that are greater than or equal to the value specified with GE.
LE (string) – The less than or equal to operator. The Evaluation results will have FilterVariable values that are less than or equal to the value specified with LE.
NE (string) – The not equal to operator. The Evaluation results will have FilterVariable values not equal to the value specified with NE.
Prefix (string) –
A string that is found at the beginning of a variable, such as Name or Id.

For example, an Evaluation could have the Name 2014-09-09-HolidayGiftMailer. To search for this Evaluation, select Name for the FilterVariable and any of the following strings for the Prefix:
- 2014-09
- 2014-09-09
- 2014-09-09-Holiday
SortOrder (string) –
A two-value parameter that determines the sequence of the resulting list of Evaluation.
- asc - Arranges the list in ascending order (A-Z, 0-9).
- dsc - Arranges the list in descending order (Z-A, 9-0).
Results are sorted by FilterVariable.
NextToken (string) – The ID of the page in the paginated results.
Limit (integer) – The maximum number of Evaluation to include in the result.

Return type:

dict

Returns:

Response Syntax

{
    'Results': [
        {
            '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'
                }
            },
            'Message': 'string',
            'ComputeTime': 123,
            'FinishedAt': datetime(2015, 1, 1),
            'StartedAt': datetime(2015, 1, 1)
        },
    ],
    'NextToken': 'string'
}

Response Structure

(dict) –

Represents the query results from a DescribeEvaluations operation. The content is essentially a list of Evaluation.
- Results (list) –
  
  A list of Evaluation that meet the search criteria.
  - (dict) –
    
    Represents the output of GetEvaluation operation.
    
    The content consists of the detailed metadata and data file information and the current status of the Evaluation.
    - EvaluationId (string) –
      
      The ID that is assigned to the Evaluation at creation.
    - MLModelId (string) –
      
      The ID of the MLModel that is the focus of the evaluation.
    - EvaluationDataSourceId (string) –
      
      The ID of the DataSource that is used to evaluate the MLModel.
    - InputDataLocationS3 (string) –
      
      The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
    - 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 Learning (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.
    - PerformanceMetrics (dict) –
      
      Measurements of how well the MLModel performed, using observations referenced by the DataSource. One of the following metrics 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.
      - Properties (dict) –
        
        (string) –
        
        (string) –
    - Message (string) –
      
      A description of the most recent details about evaluating the MLModel.
    - ComputeTime (integer) –
      
      Long integer type that is a 64-bit signed number.
    - FinishedAt (datetime) –
      
      A timestamp represented in epoch time.
    - StartedAt (datetime) –
      
      A timestamp represented in epoch time.
- NextToken (string) –
  
  The ID of the next page in the paginated results that indicates at least one more page follows.

Exceptions

MachineLearning.Client.exceptions.InvalidInputException
MachineLearning.Client.exceptions.InternalServerException