AWS SDK for C++  1.9.108
AWS SDK for C++
Public Member Functions | List of all members
Aws::ForecastService::Model::DescribePredictorResult Class Reference

#include <DescribePredictorResult.h>

Public Member Functions

 DescribePredictorResult ()
 
 DescribePredictorResult (const Aws::AmazonWebServiceResult< Aws::Utils::Json::JsonValue > &result)
 
DescribePredictorResultoperator= (const Aws::AmazonWebServiceResult< Aws::Utils::Json::JsonValue > &result)
 
const Aws::StringGetPredictorArn () const
 
void SetPredictorArn (const Aws::String &value)
 
void SetPredictorArn (Aws::String &&value)
 
void SetPredictorArn (const char *value)
 
DescribePredictorResultWithPredictorArn (const Aws::String &value)
 
DescribePredictorResultWithPredictorArn (Aws::String &&value)
 
DescribePredictorResultWithPredictorArn (const char *value)
 
const Aws::StringGetPredictorName () const
 
void SetPredictorName (const Aws::String &value)
 
void SetPredictorName (Aws::String &&value)
 
void SetPredictorName (const char *value)
 
DescribePredictorResultWithPredictorName (const Aws::String &value)
 
DescribePredictorResultWithPredictorName (Aws::String &&value)
 
DescribePredictorResultWithPredictorName (const char *value)
 
const Aws::StringGetAlgorithmArn () const
 
void SetAlgorithmArn (const Aws::String &value)
 
void SetAlgorithmArn (Aws::String &&value)
 
void SetAlgorithmArn (const char *value)
 
DescribePredictorResultWithAlgorithmArn (const Aws::String &value)
 
DescribePredictorResultWithAlgorithmArn (Aws::String &&value)
 
DescribePredictorResultWithAlgorithmArn (const char *value)
 
int GetForecastHorizon () const
 
void SetForecastHorizon (int value)
 
DescribePredictorResultWithForecastHorizon (int value)
 
const Aws::Vector< Aws::String > & GetForecastTypes () const
 
void SetForecastTypes (const Aws::Vector< Aws::String > &value)
 
void SetForecastTypes (Aws::Vector< Aws::String > &&value)
 
DescribePredictorResultWithForecastTypes (const Aws::Vector< Aws::String > &value)
 
DescribePredictorResultWithForecastTypes (Aws::Vector< Aws::String > &&value)
 
DescribePredictorResultAddForecastTypes (const Aws::String &value)
 
DescribePredictorResultAddForecastTypes (Aws::String &&value)
 
DescribePredictorResultAddForecastTypes (const char *value)
 
bool GetPerformAutoML () const
 
void SetPerformAutoML (bool value)
 
DescribePredictorResultWithPerformAutoML (bool value)
 
const AutoMLOverrideStrategyGetAutoMLOverrideStrategy () const
 
void SetAutoMLOverrideStrategy (const AutoMLOverrideStrategy &value)
 
void SetAutoMLOverrideStrategy (AutoMLOverrideStrategy &&value)
 
DescribePredictorResultWithAutoMLOverrideStrategy (const AutoMLOverrideStrategy &value)
 
DescribePredictorResultWithAutoMLOverrideStrategy (AutoMLOverrideStrategy &&value)
 
bool GetPerformHPO () const
 
void SetPerformHPO (bool value)
 
DescribePredictorResultWithPerformHPO (bool value)
 
const Aws::Map< Aws::String, Aws::String > & GetTrainingParameters () const
 
void SetTrainingParameters (const Aws::Map< Aws::String, Aws::String > &value)
 
void SetTrainingParameters (Aws::Map< Aws::String, Aws::String > &&value)
 
DescribePredictorResultWithTrainingParameters (const Aws::Map< Aws::String, Aws::String > &value)
 
DescribePredictorResultWithTrainingParameters (Aws::Map< Aws::String, Aws::String > &&value)
 
DescribePredictorResultAddTrainingParameters (const Aws::String &key, const Aws::String &value)
 
DescribePredictorResultAddTrainingParameters (Aws::String &&key, const Aws::String &value)
 
DescribePredictorResultAddTrainingParameters (const Aws::String &key, Aws::String &&value)
 
DescribePredictorResultAddTrainingParameters (Aws::String &&key, Aws::String &&value)
 
DescribePredictorResultAddTrainingParameters (const char *key, Aws::String &&value)
 
DescribePredictorResultAddTrainingParameters (Aws::String &&key, const char *value)
 
DescribePredictorResultAddTrainingParameters (const char *key, const char *value)
 
const EvaluationParametersGetEvaluationParameters () const
 
void SetEvaluationParameters (const EvaluationParameters &value)
 
void SetEvaluationParameters (EvaluationParameters &&value)
 
DescribePredictorResultWithEvaluationParameters (const EvaluationParameters &value)
 
DescribePredictorResultWithEvaluationParameters (EvaluationParameters &&value)
 
const HyperParameterTuningJobConfigGetHPOConfig () const
 
void SetHPOConfig (const HyperParameterTuningJobConfig &value)
 
void SetHPOConfig (HyperParameterTuningJobConfig &&value)
 
DescribePredictorResultWithHPOConfig (const HyperParameterTuningJobConfig &value)
 
DescribePredictorResultWithHPOConfig (HyperParameterTuningJobConfig &&value)
 
const InputDataConfigGetInputDataConfig () const
 
void SetInputDataConfig (const InputDataConfig &value)
 
void SetInputDataConfig (InputDataConfig &&value)
 
DescribePredictorResultWithInputDataConfig (const InputDataConfig &value)
 
DescribePredictorResultWithInputDataConfig (InputDataConfig &&value)
 
const FeaturizationConfigGetFeaturizationConfig () const
 
void SetFeaturizationConfig (const FeaturizationConfig &value)
 
void SetFeaturizationConfig (FeaturizationConfig &&value)
 
DescribePredictorResultWithFeaturizationConfig (const FeaturizationConfig &value)
 
DescribePredictorResultWithFeaturizationConfig (FeaturizationConfig &&value)
 
const EncryptionConfigGetEncryptionConfig () const
 
void SetEncryptionConfig (const EncryptionConfig &value)
 
void SetEncryptionConfig (EncryptionConfig &&value)
 
DescribePredictorResultWithEncryptionConfig (const EncryptionConfig &value)
 
DescribePredictorResultWithEncryptionConfig (EncryptionConfig &&value)
 
const PredictorExecutionDetailsGetPredictorExecutionDetails () const
 
void SetPredictorExecutionDetails (const PredictorExecutionDetails &value)
 
void SetPredictorExecutionDetails (PredictorExecutionDetails &&value)
 
DescribePredictorResultWithPredictorExecutionDetails (const PredictorExecutionDetails &value)
 
DescribePredictorResultWithPredictorExecutionDetails (PredictorExecutionDetails &&value)
 
long long GetEstimatedTimeRemainingInMinutes () const
 
void SetEstimatedTimeRemainingInMinutes (long long value)
 
DescribePredictorResultWithEstimatedTimeRemainingInMinutes (long long value)
 
const Aws::Vector< Aws::String > & GetDatasetImportJobArns () const
 
void SetDatasetImportJobArns (const Aws::Vector< Aws::String > &value)
 
void SetDatasetImportJobArns (Aws::Vector< Aws::String > &&value)
 
DescribePredictorResultWithDatasetImportJobArns (const Aws::Vector< Aws::String > &value)
 
DescribePredictorResultWithDatasetImportJobArns (Aws::Vector< Aws::String > &&value)
 
DescribePredictorResultAddDatasetImportJobArns (const Aws::String &value)
 
DescribePredictorResultAddDatasetImportJobArns (Aws::String &&value)
 
DescribePredictorResultAddDatasetImportJobArns (const char *value)
 
const Aws::Vector< Aws::String > & GetAutoMLAlgorithmArns () const
 
void SetAutoMLAlgorithmArns (const Aws::Vector< Aws::String > &value)
 
void SetAutoMLAlgorithmArns (Aws::Vector< Aws::String > &&value)
 
DescribePredictorResultWithAutoMLAlgorithmArns (const Aws::Vector< Aws::String > &value)
 
DescribePredictorResultWithAutoMLAlgorithmArns (Aws::Vector< Aws::String > &&value)
 
DescribePredictorResultAddAutoMLAlgorithmArns (const Aws::String &value)
 
DescribePredictorResultAddAutoMLAlgorithmArns (Aws::String &&value)
 
DescribePredictorResultAddAutoMLAlgorithmArns (const char *value)
 
const Aws::StringGetStatus () const
 
void SetStatus (const Aws::String &value)
 
void SetStatus (Aws::String &&value)
 
void SetStatus (const char *value)
 
DescribePredictorResultWithStatus (const Aws::String &value)
 
DescribePredictorResultWithStatus (Aws::String &&value)
 
DescribePredictorResultWithStatus (const char *value)
 
const Aws::StringGetMessage () const
 
void SetMessage (const Aws::String &value)
 
void SetMessage (Aws::String &&value)
 
void SetMessage (const char *value)
 
DescribePredictorResultWithMessage (const Aws::String &value)
 
DescribePredictorResultWithMessage (Aws::String &&value)
 
DescribePredictorResultWithMessage (const char *value)
 
const Aws::Utils::DateTimeGetCreationTime () const
 
void SetCreationTime (const Aws::Utils::DateTime &value)
 
void SetCreationTime (Aws::Utils::DateTime &&value)
 
DescribePredictorResultWithCreationTime (const Aws::Utils::DateTime &value)
 
DescribePredictorResultWithCreationTime (Aws::Utils::DateTime &&value)
 
const Aws::Utils::DateTimeGetLastModificationTime () const
 
void SetLastModificationTime (const Aws::Utils::DateTime &value)
 
void SetLastModificationTime (Aws::Utils::DateTime &&value)
 
DescribePredictorResultWithLastModificationTime (const Aws::Utils::DateTime &value)
 
DescribePredictorResultWithLastModificationTime (Aws::Utils::DateTime &&value)
 
const OptimizationMetricGetOptimizationMetric () const
 
void SetOptimizationMetric (const OptimizationMetric &value)
 
void SetOptimizationMetric (OptimizationMetric &&value)
 
DescribePredictorResultWithOptimizationMetric (const OptimizationMetric &value)
 
DescribePredictorResultWithOptimizationMetric (OptimizationMetric &&value)
 

Detailed Description

Definition at line 38 of file DescribePredictorResult.h.

Constructor & Destructor Documentation

◆ DescribePredictorResult() [1/2]

Aws::ForecastService::Model::DescribePredictorResult::DescribePredictorResult ( )

◆ DescribePredictorResult() [2/2]

Aws::ForecastService::Model::DescribePredictorResult::DescribePredictorResult ( const Aws::AmazonWebServiceResult< Aws::Utils::Json::JsonValue > &  result)

Member Function Documentation

◆ AddAutoMLAlgorithmArns() [1/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddAutoMLAlgorithmArns ( Aws::String &&  value)
inline

When PerformAutoML is specified, the ARN of the chosen algorithm.

Definition at line 704 of file DescribePredictorResult.h.

◆ AddAutoMLAlgorithmArns() [2/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddAutoMLAlgorithmArns ( const Aws::String value)
inline

When PerformAutoML is specified, the ARN of the chosen algorithm.

Definition at line 698 of file DescribePredictorResult.h.

◆ AddAutoMLAlgorithmArns() [3/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddAutoMLAlgorithmArns ( const char *  value)
inline

When PerformAutoML is specified, the ARN of the chosen algorithm.

Definition at line 710 of file DescribePredictorResult.h.

◆ AddDatasetImportJobArns() [1/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddDatasetImportJobArns ( Aws::String &&  value)
inline

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

Definition at line 655 of file DescribePredictorResult.h.

◆ AddDatasetImportJobArns() [2/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddDatasetImportJobArns ( const Aws::String value)
inline

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

Definition at line 649 of file DescribePredictorResult.h.

◆ AddDatasetImportJobArns() [3/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddDatasetImportJobArns ( const char *  value)
inline

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

Definition at line 661 of file DescribePredictorResult.h.

◆ AddForecastTypes() [1/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddForecastTypes ( Aws::String &&  value)
inline

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

Definition at line 213 of file DescribePredictorResult.h.

◆ AddForecastTypes() [2/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddForecastTypes ( const Aws::String value)
inline

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

Definition at line 207 of file DescribePredictorResult.h.

◆ AddForecastTypes() [3/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddForecastTypes ( const char *  value)
inline

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

Definition at line 219 of file DescribePredictorResult.h.

◆ AddTrainingParameters() [1/7]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddTrainingParameters ( Aws::String &&  key,
Aws::String &&  value 
)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 378 of file DescribePredictorResult.h.

◆ AddTrainingParameters() [2/7]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddTrainingParameters ( Aws::String &&  key,
const Aws::String value 
)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 362 of file DescribePredictorResult.h.

◆ AddTrainingParameters() [3/7]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddTrainingParameters ( Aws::String &&  key,
const char *  value 
)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 394 of file DescribePredictorResult.h.

◆ AddTrainingParameters() [4/7]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddTrainingParameters ( const Aws::String key,
Aws::String &&  value 
)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 370 of file DescribePredictorResult.h.

◆ AddTrainingParameters() [5/7]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddTrainingParameters ( const Aws::String key,
const Aws::String value 
)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 354 of file DescribePredictorResult.h.

◆ AddTrainingParameters() [6/7]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddTrainingParameters ( const char *  key,
Aws::String &&  value 
)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 386 of file DescribePredictorResult.h.

◆ AddTrainingParameters() [7/7]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::AddTrainingParameters ( const char *  key,
const char *  value 
)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 402 of file DescribePredictorResult.h.

◆ GetAlgorithmArn()

const Aws::String& Aws::ForecastService::Model::DescribePredictorResult::GetAlgorithmArn ( ) const
inline

The Amazon Resource Name (ARN) of the algorithm used for model training.

Definition at line 121 of file DescribePredictorResult.h.

◆ GetAutoMLAlgorithmArns()

const Aws::Vector<Aws::String>& Aws::ForecastService::Model::DescribePredictorResult::GetAutoMLAlgorithmArns ( ) const
inline

When PerformAutoML is specified, the ARN of the chosen algorithm.

Definition at line 668 of file DescribePredictorResult.h.

◆ GetAutoMLOverrideStrategy()

const AutoMLOverrideStrategy& Aws::ForecastService::Model::DescribePredictorResult::GetAutoMLOverrideStrategy ( ) const
inline

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

Definition at line 246 of file DescribePredictorResult.h.

◆ GetCreationTime()

const Aws::Utils::DateTime& Aws::ForecastService::Model::DescribePredictorResult::GetCreationTime ( ) const
inline

When the model training task was created.

Definition at line 837 of file DescribePredictorResult.h.

◆ GetDatasetImportJobArns()

const Aws::Vector<Aws::String>& Aws::ForecastService::Model::DescribePredictorResult::GetDatasetImportJobArns ( ) const
inline

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

Definition at line 619 of file DescribePredictorResult.h.

◆ GetEncryptionConfig()

const EncryptionConfig& Aws::ForecastService::Model::DescribePredictorResult::GetEncryptionConfig ( ) const
inline

An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

Definition at line 533 of file DescribePredictorResult.h.

◆ GetEstimatedTimeRemainingInMinutes()

long long Aws::ForecastService::Model::DescribePredictorResult::GetEstimatedTimeRemainingInMinutes ( ) const
inline

The estimated time remaining in minutes for the predictor training job to complete.

Definition at line 600 of file DescribePredictorResult.h.

◆ GetEvaluationParameters()

const EvaluationParameters& Aws::ForecastService::Model::DescribePredictorResult::GetEvaluationParameters ( ) const
inline

Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.

Definition at line 411 of file DescribePredictorResult.h.

◆ GetFeaturizationConfig()

const FeaturizationConfig& Aws::ForecastService::Model::DescribePredictorResult::GetFeaturizationConfig ( ) const
inline

The featurization configuration.

Definition at line 506 of file DescribePredictorResult.h.

◆ GetForecastHorizon()

int Aws::ForecastService::Model::DescribePredictorResult::GetForecastHorizon ( ) const
inline

The number of time-steps of the forecast. The forecast horizon is also called the prediction length.

Definition at line 158 of file DescribePredictorResult.h.

◆ GetForecastTypes()

const Aws::Vector<Aws::String>& Aws::ForecastService::Model::DescribePredictorResult::GetForecastTypes ( ) const
inline

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

Definition at line 177 of file DescribePredictorResult.h.

◆ GetHPOConfig()

const HyperParameterTuningJobConfig& Aws::ForecastService::Model::DescribePredictorResult::GetHPOConfig ( ) const
inline

The hyperparameter override values for the algorithm.

Definition at line 449 of file DescribePredictorResult.h.

◆ GetInputDataConfig()

const InputDataConfig& Aws::ForecastService::Model::DescribePredictorResult::GetInputDataConfig ( ) const
inline

Describes the dataset group that contains the data to use to train the predictor.

Definition at line 476 of file DescribePredictorResult.h.

◆ GetLastModificationTime()

const Aws::Utils::DateTime& Aws::ForecastService::Model::DescribePredictorResult::GetLastModificationTime ( ) const
inline

The last time the resource was modified. The timestamp depends on the status of the job:

  • CREATE_PENDING - The CreationTime.

  • CREATE_IN_PROGRESS - The current timestamp.

  • CREATE_STOPPING - The current timestamp.

  • CREATE_STOPPED - When the job stopped.

  • ACTIVE or CREATE_FAILED - When the job finished or failed.

Definition at line 869 of file DescribePredictorResult.h.

◆ GetMessage()

const Aws::String& Aws::ForecastService::Model::DescribePredictorResult::GetMessage ( ) const
inline

If an error occurred, an informational message about the error.

Definition at line 801 of file DescribePredictorResult.h.

◆ GetOptimizationMetric()

const OptimizationMetric& Aws::ForecastService::Model::DescribePredictorResult::GetOptimizationMetric ( ) const
inline

The accuracy metric used to optimize the predictor.

Definition at line 919 of file DescribePredictorResult.h.

◆ GetPerformAutoML()

bool Aws::ForecastService::Model::DescribePredictorResult::GetPerformAutoML ( ) const
inline

Whether the predictor is set to perform AutoML.

Definition at line 225 of file DescribePredictorResult.h.

◆ GetPerformHPO()

bool Aws::ForecastService::Model::DescribePredictorResult::GetPerformHPO ( ) const
inline

Whether the predictor is set to perform hyperparameter optimization (HPO).

Definition at line 293 of file DescribePredictorResult.h.

◆ GetPredictorArn()

const Aws::String& Aws::ForecastService::Model::DescribePredictorResult::GetPredictorArn ( ) const
inline

The ARN of the predictor.

Definition at line 49 of file DescribePredictorResult.h.

◆ GetPredictorExecutionDetails()

const PredictorExecutionDetails& Aws::ForecastService::Model::DescribePredictorResult::GetPredictorExecutionDetails ( ) const
inline

Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor. You specify the number of backtests to perform when you call the operation.

Definition at line 565 of file DescribePredictorResult.h.

◆ GetPredictorName()

const Aws::String& Aws::ForecastService::Model::DescribePredictorResult::GetPredictorName ( ) const
inline

The name of the predictor.

Definition at line 85 of file DescribePredictorResult.h.

◆ GetStatus()

const Aws::String& Aws::ForecastService::Model::DescribePredictorResult::GetStatus ( ) const
inline

The status of the predictor. States include:

  • ACTIVE

  • CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED

  • DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

  • CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

Definition at line 723 of file DescribePredictorResult.h.

◆ GetTrainingParameters()

const Aws::Map<Aws::String, Aws::String>& Aws::ForecastService::Model::DescribePredictorResult::GetTrainingParameters ( ) const
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 314 of file DescribePredictorResult.h.

◆ operator=()

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::operator= ( const Aws::AmazonWebServiceResult< Aws::Utils::Json::JsonValue > &  result)

◆ SetAlgorithmArn() [1/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetAlgorithmArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the algorithm used for model training.

Definition at line 131 of file DescribePredictorResult.h.

◆ SetAlgorithmArn() [2/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetAlgorithmArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the algorithm used for model training.

Definition at line 126 of file DescribePredictorResult.h.

◆ SetAlgorithmArn() [3/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetAlgorithmArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the algorithm used for model training.

Definition at line 136 of file DescribePredictorResult.h.

◆ SetAutoMLAlgorithmArns() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetAutoMLAlgorithmArns ( Aws::Vector< Aws::String > &&  value)
inline

When PerformAutoML is specified, the ARN of the chosen algorithm.

Definition at line 680 of file DescribePredictorResult.h.

◆ SetAutoMLAlgorithmArns() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetAutoMLAlgorithmArns ( const Aws::Vector< Aws::String > &  value)
inline

When PerformAutoML is specified, the ARN of the chosen algorithm.

Definition at line 674 of file DescribePredictorResult.h.

◆ SetAutoMLOverrideStrategy() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetAutoMLOverrideStrategy ( AutoMLOverrideStrategy &&  value)
inline

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

Definition at line 266 of file DescribePredictorResult.h.

◆ SetAutoMLOverrideStrategy() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetAutoMLOverrideStrategy ( const AutoMLOverrideStrategy value)
inline

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

Definition at line 256 of file DescribePredictorResult.h.

◆ SetCreationTime() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetCreationTime ( Aws::Utils::DateTime &&  value)
inline

When the model training task was created.

Definition at line 847 of file DescribePredictorResult.h.

◆ SetCreationTime() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetCreationTime ( const Aws::Utils::DateTime value)
inline

When the model training task was created.

Definition at line 842 of file DescribePredictorResult.h.

◆ SetDatasetImportJobArns() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetDatasetImportJobArns ( Aws::Vector< Aws::String > &&  value)
inline

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

Definition at line 631 of file DescribePredictorResult.h.

◆ SetDatasetImportJobArns() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetDatasetImportJobArns ( const Aws::Vector< Aws::String > &  value)
inline

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

Definition at line 625 of file DescribePredictorResult.h.

◆ SetEncryptionConfig() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetEncryptionConfig ( const EncryptionConfig value)
inline

An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

Definition at line 539 of file DescribePredictorResult.h.

◆ SetEncryptionConfig() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetEncryptionConfig ( EncryptionConfig &&  value)
inline

An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

Definition at line 545 of file DescribePredictorResult.h.

◆ SetEstimatedTimeRemainingInMinutes()

void Aws::ForecastService::Model::DescribePredictorResult::SetEstimatedTimeRemainingInMinutes ( long long  value)
inline

The estimated time remaining in minutes for the predictor training job to complete.

Definition at line 606 of file DescribePredictorResult.h.

◆ SetEvaluationParameters() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetEvaluationParameters ( const EvaluationParameters value)
inline

Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.

Definition at line 419 of file DescribePredictorResult.h.

◆ SetEvaluationParameters() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetEvaluationParameters ( EvaluationParameters &&  value)
inline

Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.

Definition at line 427 of file DescribePredictorResult.h.

◆ SetFeaturizationConfig() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetFeaturizationConfig ( const FeaturizationConfig value)
inline

The featurization configuration.

Definition at line 511 of file DescribePredictorResult.h.

◆ SetFeaturizationConfig() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetFeaturizationConfig ( FeaturizationConfig &&  value)
inline

The featurization configuration.

Definition at line 516 of file DescribePredictorResult.h.

◆ SetForecastHorizon()

void Aws::ForecastService::Model::DescribePredictorResult::SetForecastHorizon ( int  value)
inline

The number of time-steps of the forecast. The forecast horizon is also called the prediction length.

Definition at line 164 of file DescribePredictorResult.h.

◆ SetForecastTypes() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetForecastTypes ( Aws::Vector< Aws::String > &&  value)
inline

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

Definition at line 189 of file DescribePredictorResult.h.

◆ SetForecastTypes() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetForecastTypes ( const Aws::Vector< Aws::String > &  value)
inline

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

Definition at line 183 of file DescribePredictorResult.h.

◆ SetHPOConfig() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetHPOConfig ( const HyperParameterTuningJobConfig value)
inline

The hyperparameter override values for the algorithm.

Definition at line 454 of file DescribePredictorResult.h.

◆ SetHPOConfig() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetHPOConfig ( HyperParameterTuningJobConfig &&  value)
inline

The hyperparameter override values for the algorithm.

Definition at line 459 of file DescribePredictorResult.h.

◆ SetInputDataConfig() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetInputDataConfig ( const InputDataConfig value)
inline

Describes the dataset group that contains the data to use to train the predictor.

Definition at line 482 of file DescribePredictorResult.h.

◆ SetInputDataConfig() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetInputDataConfig ( InputDataConfig &&  value)
inline

Describes the dataset group that contains the data to use to train the predictor.

Definition at line 488 of file DescribePredictorResult.h.

◆ SetLastModificationTime() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetLastModificationTime ( Aws::Utils::DateTime &&  value)
inline

The last time the resource was modified. The timestamp depends on the status of the job:

  • CREATE_PENDING - The CreationTime.

  • CREATE_IN_PROGRESS - The current timestamp.

  • CREATE_STOPPING - The current timestamp.

  • CREATE_STOPPED - When the job stopped.

  • ACTIVE or CREATE_FAILED - When the job finished or failed.

Definition at line 891 of file DescribePredictorResult.h.

◆ SetLastModificationTime() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetLastModificationTime ( const Aws::Utils::DateTime value)
inline

The last time the resource was modified. The timestamp depends on the status of the job:

  • CREATE_PENDING - The CreationTime.

  • CREATE_IN_PROGRESS - The current timestamp.

  • CREATE_STOPPING - The current timestamp.

  • CREATE_STOPPED - When the job stopped.

  • ACTIVE or CREATE_FAILED - When the job finished or failed.

Definition at line 880 of file DescribePredictorResult.h.

◆ SetMessage() [1/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetMessage ( Aws::String &&  value)
inline

If an error occurred, an informational message about the error.

Definition at line 811 of file DescribePredictorResult.h.

◆ SetMessage() [2/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetMessage ( const Aws::String value)
inline

If an error occurred, an informational message about the error.

Definition at line 806 of file DescribePredictorResult.h.

◆ SetMessage() [3/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetMessage ( const char *  value)
inline

If an error occurred, an informational message about the error.

Definition at line 816 of file DescribePredictorResult.h.

◆ SetOptimizationMetric() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetOptimizationMetric ( const OptimizationMetric value)
inline

The accuracy metric used to optimize the predictor.

Definition at line 924 of file DescribePredictorResult.h.

◆ SetOptimizationMetric() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetOptimizationMetric ( OptimizationMetric &&  value)
inline

The accuracy metric used to optimize the predictor.

Definition at line 929 of file DescribePredictorResult.h.

◆ SetPerformAutoML()

void Aws::ForecastService::Model::DescribePredictorResult::SetPerformAutoML ( bool  value)
inline

Whether the predictor is set to perform AutoML.

Definition at line 230 of file DescribePredictorResult.h.

◆ SetPerformHPO()

void Aws::ForecastService::Model::DescribePredictorResult::SetPerformHPO ( bool  value)
inline

Whether the predictor is set to perform hyperparameter optimization (HPO).

Definition at line 299 of file DescribePredictorResult.h.

◆ SetPredictorArn() [1/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetPredictorArn ( Aws::String &&  value)
inline

The ARN of the predictor.

Definition at line 59 of file DescribePredictorResult.h.

◆ SetPredictorArn() [2/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetPredictorArn ( const Aws::String value)
inline

The ARN of the predictor.

Definition at line 54 of file DescribePredictorResult.h.

◆ SetPredictorArn() [3/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetPredictorArn ( const char *  value)
inline

The ARN of the predictor.

Definition at line 64 of file DescribePredictorResult.h.

◆ SetPredictorExecutionDetails() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetPredictorExecutionDetails ( const PredictorExecutionDetails value)
inline

Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor. You specify the number of backtests to perform when you call the operation.

Definition at line 572 of file DescribePredictorResult.h.

◆ SetPredictorExecutionDetails() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetPredictorExecutionDetails ( PredictorExecutionDetails &&  value)
inline

Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor. You specify the number of backtests to perform when you call the operation.

Definition at line 579 of file DescribePredictorResult.h.

◆ SetPredictorName() [1/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetPredictorName ( Aws::String &&  value)
inline

The name of the predictor.

Definition at line 95 of file DescribePredictorResult.h.

◆ SetPredictorName() [2/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetPredictorName ( const Aws::String value)
inline

The name of the predictor.

Definition at line 90 of file DescribePredictorResult.h.

◆ SetPredictorName() [3/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetPredictorName ( const char *  value)
inline

The name of the predictor.

Definition at line 100 of file DescribePredictorResult.h.

◆ SetStatus() [1/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetStatus ( Aws::String &&  value)
inline

The status of the predictor. States include:

  • ACTIVE

  • CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED

  • DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

  • CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

Definition at line 747 of file DescribePredictorResult.h.

◆ SetStatus() [2/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetStatus ( const Aws::String value)
inline

The status of the predictor. States include:

  • ACTIVE

  • CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED

  • DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

  • CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

Definition at line 735 of file DescribePredictorResult.h.

◆ SetStatus() [3/3]

void Aws::ForecastService::Model::DescribePredictorResult::SetStatus ( const char *  value)
inline

The status of the predictor. States include:

  • ACTIVE

  • CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED

  • DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

  • CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

Definition at line 759 of file DescribePredictorResult.h.

◆ SetTrainingParameters() [1/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetTrainingParameters ( Aws::Map< Aws::String, Aws::String > &&  value)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 330 of file DescribePredictorResult.h.

◆ SetTrainingParameters() [2/2]

void Aws::ForecastService::Model::DescribePredictorResult::SetTrainingParameters ( const Aws::Map< Aws::String, Aws::String > &  value)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 322 of file DescribePredictorResult.h.

◆ WithAlgorithmArn() [1/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithAlgorithmArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the algorithm used for model training.

Definition at line 146 of file DescribePredictorResult.h.

◆ WithAlgorithmArn() [2/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithAlgorithmArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the algorithm used for model training.

Definition at line 141 of file DescribePredictorResult.h.

◆ WithAlgorithmArn() [3/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithAlgorithmArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the algorithm used for model training.

Definition at line 151 of file DescribePredictorResult.h.

◆ WithAutoMLAlgorithmArns() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithAutoMLAlgorithmArns ( Aws::Vector< Aws::String > &&  value)
inline

When PerformAutoML is specified, the ARN of the chosen algorithm.

Definition at line 692 of file DescribePredictorResult.h.

◆ WithAutoMLAlgorithmArns() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithAutoMLAlgorithmArns ( const Aws::Vector< Aws::String > &  value)
inline

When PerformAutoML is specified, the ARN of the chosen algorithm.

Definition at line 686 of file DescribePredictorResult.h.

◆ WithAutoMLOverrideStrategy() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithAutoMLOverrideStrategy ( AutoMLOverrideStrategy &&  value)
inline

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

Definition at line 286 of file DescribePredictorResult.h.

◆ WithAutoMLOverrideStrategy() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithAutoMLOverrideStrategy ( const AutoMLOverrideStrategy value)
inline

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

Definition at line 276 of file DescribePredictorResult.h.

◆ WithCreationTime() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithCreationTime ( Aws::Utils::DateTime &&  value)
inline

When the model training task was created.

Definition at line 857 of file DescribePredictorResult.h.

◆ WithCreationTime() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithCreationTime ( const Aws::Utils::DateTime value)
inline

When the model training task was created.

Definition at line 852 of file DescribePredictorResult.h.

◆ WithDatasetImportJobArns() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithDatasetImportJobArns ( Aws::Vector< Aws::String > &&  value)
inline

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

Definition at line 643 of file DescribePredictorResult.h.

◆ WithDatasetImportJobArns() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithDatasetImportJobArns ( const Aws::Vector< Aws::String > &  value)
inline

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

Definition at line 637 of file DescribePredictorResult.h.

◆ WithEncryptionConfig() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithEncryptionConfig ( const EncryptionConfig value)
inline

An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

Definition at line 551 of file DescribePredictorResult.h.

◆ WithEncryptionConfig() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithEncryptionConfig ( EncryptionConfig &&  value)
inline

An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

Definition at line 557 of file DescribePredictorResult.h.

◆ WithEstimatedTimeRemainingInMinutes()

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithEstimatedTimeRemainingInMinutes ( long long  value)
inline

The estimated time remaining in minutes for the predictor training job to complete.

Definition at line 612 of file DescribePredictorResult.h.

◆ WithEvaluationParameters() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithEvaluationParameters ( const EvaluationParameters value)
inline

Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.

Definition at line 435 of file DescribePredictorResult.h.

◆ WithEvaluationParameters() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithEvaluationParameters ( EvaluationParameters &&  value)
inline

Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.

Definition at line 443 of file DescribePredictorResult.h.

◆ WithFeaturizationConfig() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithFeaturizationConfig ( const FeaturizationConfig value)
inline

The featurization configuration.

Definition at line 521 of file DescribePredictorResult.h.

◆ WithFeaturizationConfig() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithFeaturizationConfig ( FeaturizationConfig &&  value)
inline

The featurization configuration.

Definition at line 526 of file DescribePredictorResult.h.

◆ WithForecastHorizon()

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithForecastHorizon ( int  value)
inline

The number of time-steps of the forecast. The forecast horizon is also called the prediction length.

Definition at line 170 of file DescribePredictorResult.h.

◆ WithForecastTypes() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithForecastTypes ( Aws::Vector< Aws::String > &&  value)
inline

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

Definition at line 201 of file DescribePredictorResult.h.

◆ WithForecastTypes() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithForecastTypes ( const Aws::Vector< Aws::String > &  value)
inline

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

Definition at line 195 of file DescribePredictorResult.h.

◆ WithHPOConfig() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithHPOConfig ( const HyperParameterTuningJobConfig value)
inline

The hyperparameter override values for the algorithm.

Definition at line 464 of file DescribePredictorResult.h.

◆ WithHPOConfig() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithHPOConfig ( HyperParameterTuningJobConfig &&  value)
inline

The hyperparameter override values for the algorithm.

Definition at line 469 of file DescribePredictorResult.h.

◆ WithInputDataConfig() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithInputDataConfig ( const InputDataConfig value)
inline

Describes the dataset group that contains the data to use to train the predictor.

Definition at line 494 of file DescribePredictorResult.h.

◆ WithInputDataConfig() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithInputDataConfig ( InputDataConfig &&  value)
inline

Describes the dataset group that contains the data to use to train the predictor.

Definition at line 500 of file DescribePredictorResult.h.

◆ WithLastModificationTime() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithLastModificationTime ( Aws::Utils::DateTime &&  value)
inline

The last time the resource was modified. The timestamp depends on the status of the job:

  • CREATE_PENDING - The CreationTime.

  • CREATE_IN_PROGRESS - The current timestamp.

  • CREATE_STOPPING - The current timestamp.

  • CREATE_STOPPED - When the job stopped.

  • ACTIVE or CREATE_FAILED - When the job finished or failed.

Definition at line 913 of file DescribePredictorResult.h.

◆ WithLastModificationTime() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithLastModificationTime ( const Aws::Utils::DateTime value)
inline

The last time the resource was modified. The timestamp depends on the status of the job:

  • CREATE_PENDING - The CreationTime.

  • CREATE_IN_PROGRESS - The current timestamp.

  • CREATE_STOPPING - The current timestamp.

  • CREATE_STOPPED - When the job stopped.

  • ACTIVE or CREATE_FAILED - When the job finished or failed.

Definition at line 902 of file DescribePredictorResult.h.

◆ WithMessage() [1/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithMessage ( Aws::String &&  value)
inline

If an error occurred, an informational message about the error.

Definition at line 826 of file DescribePredictorResult.h.

◆ WithMessage() [2/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithMessage ( const Aws::String value)
inline

If an error occurred, an informational message about the error.

Definition at line 821 of file DescribePredictorResult.h.

◆ WithMessage() [3/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithMessage ( const char *  value)
inline

If an error occurred, an informational message about the error.

Definition at line 831 of file DescribePredictorResult.h.

◆ WithOptimizationMetric() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithOptimizationMetric ( const OptimizationMetric value)
inline

The accuracy metric used to optimize the predictor.

Definition at line 934 of file DescribePredictorResult.h.

◆ WithOptimizationMetric() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithOptimizationMetric ( OptimizationMetric &&  value)
inline

The accuracy metric used to optimize the predictor.

Definition at line 939 of file DescribePredictorResult.h.

◆ WithPerformAutoML()

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPerformAutoML ( bool  value)
inline

Whether the predictor is set to perform AutoML.

Definition at line 235 of file DescribePredictorResult.h.

◆ WithPerformHPO()

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPerformHPO ( bool  value)
inline

Whether the predictor is set to perform hyperparameter optimization (HPO).

Definition at line 305 of file DescribePredictorResult.h.

◆ WithPredictorArn() [1/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPredictorArn ( Aws::String &&  value)
inline

The ARN of the predictor.

Definition at line 74 of file DescribePredictorResult.h.

◆ WithPredictorArn() [2/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPredictorArn ( const Aws::String value)
inline

The ARN of the predictor.

Definition at line 69 of file DescribePredictorResult.h.

◆ WithPredictorArn() [3/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPredictorArn ( const char *  value)
inline

The ARN of the predictor.

Definition at line 79 of file DescribePredictorResult.h.

◆ WithPredictorExecutionDetails() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPredictorExecutionDetails ( const PredictorExecutionDetails value)
inline

Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor. You specify the number of backtests to perform when you call the operation.

Definition at line 586 of file DescribePredictorResult.h.

◆ WithPredictorExecutionDetails() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPredictorExecutionDetails ( PredictorExecutionDetails &&  value)
inline

Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor. You specify the number of backtests to perform when you call the operation.

Definition at line 593 of file DescribePredictorResult.h.

◆ WithPredictorName() [1/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPredictorName ( Aws::String &&  value)
inline

The name of the predictor.

Definition at line 110 of file DescribePredictorResult.h.

◆ WithPredictorName() [2/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPredictorName ( const Aws::String value)
inline

The name of the predictor.

Definition at line 105 of file DescribePredictorResult.h.

◆ WithPredictorName() [3/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithPredictorName ( const char *  value)
inline

The name of the predictor.

Definition at line 115 of file DescribePredictorResult.h.

◆ WithStatus() [1/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithStatus ( Aws::String &&  value)
inline

The status of the predictor. States include:

  • ACTIVE

  • CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED

  • DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

  • CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

Definition at line 783 of file DescribePredictorResult.h.

◆ WithStatus() [2/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithStatus ( const Aws::String value)
inline

The status of the predictor. States include:

  • ACTIVE

  • CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED

  • DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

  • CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

Definition at line 771 of file DescribePredictorResult.h.

◆ WithStatus() [3/3]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithStatus ( const char *  value)
inline

The status of the predictor. States include:

  • ACTIVE

  • CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED

  • DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

  • CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

Definition at line 795 of file DescribePredictorResult.h.

◆ WithTrainingParameters() [1/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithTrainingParameters ( Aws::Map< Aws::String, Aws::String > &&  value)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 346 of file DescribePredictorResult.h.

◆ WithTrainingParameters() [2/2]

DescribePredictorResult& Aws::ForecastService::Model::DescribePredictorResult::WithTrainingParameters ( const Aws::Map< Aws::String, Aws::String > &  value)
inline

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

Definition at line 338 of file DescribePredictorResult.h.


The documentation for this class was generated from the following file: