GetEvaluationOutput ¶

class GetEvaluationOutput(TypedDict, closed=True):
    evaluation_id: NotRequired["capo_machine_learning.types.entity_id.EntityId"]
    """<p>The evaluation ID which is same as the <code>EvaluationId</code> in the request.</p>"""
    ml_model_id: NotRequired["capo_machine_learning.types.entity_id.EntityId"]
    """<p>The ID of the <code>MLModel</code> that was the focus of the evaluation.</p>"""
    evaluation_data_source_id: NotRequired[
        "capo_machine_learning.types.entity_id.EntityId"
    ]
    """<p>The <code>DataSource</code> used for this evaluation.</p>"""
    input_data_location_s3: NotRequired["capo_machine_learning.types.s3_url.S3Url"]
    """<p>The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).</p>"""
    created_by_iam_user: NotRequired[
        "capo_machine_learning.types.aws_user_arn.AwsUserArn"
    ]
    """<p>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.</p>"""
    created_at: NotRequired["capo_machine_learning.types.epoch_time.EpochTime"]
    """<p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>"""
    last_updated_at: NotRequired["capo_machine_learning.types.epoch_time.EpochTime"]
    """<p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>"""
    name: NotRequired["capo_machine_learning.types.entity_name.EntityName"]
    """<p>A user-supplied name or description of the <code>Evaluation</code>. </p>"""
    status: NotRequired["capo_machine_learning.types.entity_status.EntityStatus"]
    """<p>The status of the evaluation. This element can have one of the following values:</p> <ul> <li> <p> <code>PENDING</code> - Amazon Machine Language (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p> </li> <li> <p> <code>INPROGRESS</code> - The evaluation is underway.</p> </li> <li> <p> <code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p> </li> <li> <p> <code>COMPLETED</code> - The evaluation process completed successfully.</p> </li> <li> <p> <code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p> </li> </ul>"""
    performance_metrics: NotRequired[
        "capo_machine_learning.types.performance_metrics.PerformanceMetrics"
    ]
    """<p>Measurements of how well the <code>MLModel</code> performed using observations referenced by the <code>DataSource</code>. One of the following metric is returned based on the type of the <code>MLModel</code>: </p> <ul> <li> <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance. </p> </li> <li> <p>RegressionRMSE: A regression <code>MLModel</code> uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.</p> </li> <li> <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance. </p> </li> </ul> <p> For more information about performance metrics, please see the <a href="https://docs.aws.amazon.com/machine-learning/latest/dg">Amazon Machine Learning Developer Guide</a>. </p>"""
    log_uri: NotRequired["capo_machine_learning.types.presigned_s3_url.PresignedS3Url"]
    """<p>A link to the file that contains logs of the <code>CreateEvaluation</code> operation.</p>"""
    message: NotRequired["capo_machine_learning.types.message.Message"]
    """<p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>"""
    compute_time: NotRequired["capo_machine_learning.types.long_type.LongType"]
    """<p>The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the <code>Evaluation</code>, normalized and scaled on computation resources. <code>ComputeTime</code> is only available if the <code>Evaluation</code> is in the <code>COMPLETED</code> state.</p>"""
    finished_at: NotRequired["capo_machine_learning.types.epoch_time.EpochTime"]
    """<p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>COMPLETED</code> or <code>FAILED</code>. <code>FinishedAt</code> is only available when the <code>Evaluation</code> is in the <code>COMPLETED</code> or <code>FAILED</code> state.</p>"""
    started_at: NotRequired["capo_machine_learning.types.epoch_time.EpochTime"]
    """<p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>INPROGRESS</code>. <code>StartedAt</code> isn't available if the <code>Evaluation</code> is in the <code>PENDING</code> state.</p>"""