List the candidates created for the job¶

Description¶

List the candidates created for the job.

Usage¶

sagemaker_list_candidates_for_auto_ml_job(AutoMLJobName, StatusEquals,
  CandidateNameEquals, SortOrder, SortBy, MaxResults, NextToken)

Arguments¶

AutoMLJobName

[required] List the candidates created for the job by providing the job's name.
StatusEquals

List the candidates for the job and filter by status.
CandidateNameEquals

List the candidates for the job and filter by candidate name.
SortOrder

The sort order for the results. The default is Ascending.
SortBy

The parameter by which to sort the results. The default is Descending.
MaxResults

List the job's candidates up to a specified limit.
NextToken

If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.

Value¶

A list with the following syntax:

list(
  Candidates = list(
    list(
      CandidateName = "string",
      FinalAutoMLJobObjectiveMetric = list(
        Type = "Maximize"|"Minimize",
        MetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"BalancedAccuracy"|"R2"|"Recall"|"RecallMacro"|"Precision"|"PrecisionMacro"|"MAE"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss",
        Value = 123.0,
        StandardMetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"BalancedAccuracy"|"R2"|"Recall"|"RecallMacro"|"Precision"|"PrecisionMacro"|"MAE"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss"
      ),
      ObjectiveStatus = "Succeeded"|"Pending"|"Failed",
      CandidateSteps = list(
        list(
          CandidateStepType = "AWS::SageMaker::TrainingJob"|"AWS::SageMaker::TransformJob"|"AWS::SageMaker::ProcessingJob",
          CandidateStepArn = "string",
          CandidateStepName = "string"
        )
      ),
      CandidateStatus = "Completed"|"InProgress"|"Failed"|"Stopped"|"Stopping",
      InferenceContainers = list(
        list(
          Image = "string",
          ModelDataUrl = "string",
          Environment = list(
            "string"
          )
        )
      ),
      CreationTime = as.POSIXct(
        "2015-01-01"
      ),
      EndTime = as.POSIXct(
        "2015-01-01"
      ),
      LastModifiedTime = as.POSIXct(
        "2015-01-01"
      ),
      FailureReason = "string",
      CandidateProperties = list(
        CandidateArtifactLocations = list(
          Explainability = "string",
          ModelInsights = "string",
          BacktestResults = "string"
        ),
        CandidateMetrics = list(
          list(
            MetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"BalancedAccuracy"|"R2"|"Recall"|"RecallMacro"|"Precision"|"PrecisionMacro"|"MAE"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss",
            StandardMetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"MAE"|"R2"|"BalancedAccuracy"|"Precision"|"PrecisionMacro"|"Recall"|"RecallMacro"|"LogLoss"|"InferenceLatency"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss"|"Rouge1"|"Rouge2"|"RougeL"|"RougeLSum"|"Perplexity"|"ValidationLoss"|"TrainingLoss",
            Value = 123.0,
            Set = "Train"|"Validation"|"Test"
          )
        )
      ),
      InferenceContainerDefinitions = list(
        list(
          list(
            Image = "string",
            ModelDataUrl = "string",
            Environment = list(
              "string"
            )
          )
        )
      )
    )
  ),
  NextToken = "string"
)

Request syntax¶

svc$list_candidates_for_auto_ml_job(
  AutoMLJobName = "string",
  StatusEquals = "Completed"|"InProgress"|"Failed"|"Stopped"|"Stopping",
  CandidateNameEquals = "string",
  SortOrder = "Ascending"|"Descending",
  SortBy = "CreationTime"|"Status"|"FinalObjectiveMetricValue",
  MaxResults = 123,
  NextToken = "string"
)