public static interface DescribePredictorResponse.Builder extends ForecastResponse.Builder, SdkPojo, CopyableBuilder<DescribePredictorResponse.Builder,DescribePredictorResponse>
| Modifier and Type | Method and Description |
|---|---|
DescribePredictorResponse.Builder |
algorithmArn(String algorithmArn)
The Amazon Resource Name (ARN) of the algorithm used for model training.
|
DescribePredictorResponse.Builder |
autoMLAlgorithmArns(Collection<String> autoMLAlgorithmArns)
When
PerformAutoML is specified, the ARN of the chosen algorithm. |
DescribePredictorResponse.Builder |
autoMLAlgorithmArns(String... autoMLAlgorithmArns)
When
PerformAutoML is specified, the ARN of the chosen algorithm. |
DescribePredictorResponse.Builder |
autoMLOverrideStrategy(AutoMLOverrideStrategy autoMLOverrideStrategy)
|
DescribePredictorResponse.Builder |
autoMLOverrideStrategy(String autoMLOverrideStrategy)
|
DescribePredictorResponse.Builder |
creationTime(Instant creationTime)
When the model training task was created.
|
DescribePredictorResponse.Builder |
datasetImportJobArns(Collection<String> datasetImportJobArns)
An array of the ARNs of the dataset import jobs used to import training data for the predictor.
|
DescribePredictorResponse.Builder |
datasetImportJobArns(String... datasetImportJobArns)
An array of the ARNs of the dataset import jobs used to import training data for the predictor.
|
default DescribePredictorResponse.Builder |
encryptionConfig(Consumer<EncryptionConfig.Builder> encryptionConfig)
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast
can assume to access the key.
|
DescribePredictorResponse.Builder |
encryptionConfig(EncryptionConfig encryptionConfig)
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast
can assume to access the key.
|
DescribePredictorResponse.Builder |
estimatedTimeRemainingInMinutes(Long estimatedTimeRemainingInMinutes)
The estimated time remaining in minutes for the predictor training job to complete.
|
default DescribePredictorResponse.Builder |
evaluationParameters(Consumer<EvaluationParameters.Builder> evaluationParameters)
Used to override the default evaluation parameters of the specified algorithm.
|
DescribePredictorResponse.Builder |
evaluationParameters(EvaluationParameters evaluationParameters)
Used to override the default evaluation parameters of the specified algorithm.
|
default DescribePredictorResponse.Builder |
featurizationConfig(Consumer<FeaturizationConfig.Builder> featurizationConfig)
The featurization configuration.
|
DescribePredictorResponse.Builder |
featurizationConfig(FeaturizationConfig featurizationConfig)
The featurization configuration.
|
DescribePredictorResponse.Builder |
forecastHorizon(Integer forecastHorizon)
The number of time-steps of the forecast.
|
DescribePredictorResponse.Builder |
forecastTypes(Collection<String> forecastTypes)
The forecast types used during predictor training.
|
DescribePredictorResponse.Builder |
forecastTypes(String... forecastTypes)
The forecast types used during predictor training.
|
default DescribePredictorResponse.Builder |
hpoConfig(Consumer<HyperParameterTuningJobConfig.Builder> hpoConfig)
The hyperparameter override values for the algorithm.
|
DescribePredictorResponse.Builder |
hpoConfig(HyperParameterTuningJobConfig hpoConfig)
The hyperparameter override values for the algorithm.
|
default DescribePredictorResponse.Builder |
inputDataConfig(Consumer<InputDataConfig.Builder> inputDataConfig)
Describes the dataset group that contains the data to use to train the predictor.
|
DescribePredictorResponse.Builder |
inputDataConfig(InputDataConfig inputDataConfig)
Describes the dataset group that contains the data to use to train the predictor.
|
DescribePredictorResponse.Builder |
isAutoPredictor(Boolean isAutoPredictor)
Whether the predictor was created with CreateAutoPredictor.
|
DescribePredictorResponse.Builder |
lastModificationTime(Instant lastModificationTime)
The last time the resource was modified.
|
DescribePredictorResponse.Builder |
message(String message)
If an error occurred, an informational message about the error.
|
DescribePredictorResponse.Builder |
optimizationMetric(OptimizationMetric optimizationMetric)
The accuracy metric used to optimize the predictor.
|
DescribePredictorResponse.Builder |
optimizationMetric(String optimizationMetric)
The accuracy metric used to optimize the predictor.
|
DescribePredictorResponse.Builder |
performAutoML(Boolean performAutoML)
Whether the predictor is set to perform AutoML.
|
DescribePredictorResponse.Builder |
performHPO(Boolean performHPO)
Whether the predictor is set to perform hyperparameter optimization (HPO).
|
DescribePredictorResponse.Builder |
predictorArn(String predictorArn)
The ARN of the predictor.
|
default DescribePredictorResponse.Builder |
predictorExecutionDetails(Consumer<PredictorExecutionDetails.Builder> predictorExecutionDetails)
Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor.
|
DescribePredictorResponse.Builder |
predictorExecutionDetails(PredictorExecutionDetails predictorExecutionDetails)
Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor.
|
DescribePredictorResponse.Builder |
predictorName(String predictorName)
The name of the predictor.
|
DescribePredictorResponse.Builder |
status(String status)
The status of the predictor.
|
DescribePredictorResponse.Builder |
trainingParameters(Map<String,String> trainingParameters)
The default training parameters or overrides selected during model training.
|
build, responseMetadata, responseMetadatasdkHttpResponse, sdkHttpResponseequalsBySdkFields, sdkFieldscopyapplyMutation, buildDescribePredictorResponse.Builder predictorArn(String predictorArn)
The ARN of the predictor.
predictorArn - The ARN of the predictor.DescribePredictorResponse.Builder predictorName(String predictorName)
The name of the predictor.
predictorName - The name of the predictor.DescribePredictorResponse.Builder algorithmArn(String algorithmArn)
The Amazon Resource Name (ARN) of the algorithm used for model training.
algorithmArn - The Amazon Resource Name (ARN) of the algorithm used for model training.DescribePredictorResponse.Builder autoMLAlgorithmArns(Collection<String> autoMLAlgorithmArns)
When PerformAutoML is specified, the ARN of the chosen algorithm.
autoMLAlgorithmArns - When PerformAutoML is specified, the ARN of the chosen algorithm.DescribePredictorResponse.Builder autoMLAlgorithmArns(String... autoMLAlgorithmArns)
When PerformAutoML is specified, the ARN of the chosen algorithm.
autoMLAlgorithmArns - When PerformAutoML is specified, the ARN of the chosen algorithm.DescribePredictorResponse.Builder forecastHorizon(Integer forecastHorizon)
The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
forecastHorizon - The number of time-steps of the forecast. The forecast horizon is also called the prediction length.DescribePredictorResponse.Builder forecastTypes(Collection<String> forecastTypes)
The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
forecastTypes - The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]DescribePredictorResponse.Builder forecastTypes(String... forecastTypes)
The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
forecastTypes - The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]DescribePredictorResponse.Builder performAutoML(Boolean performAutoML)
Whether the predictor is set to perform AutoML.
performAutoML - Whether the predictor is set to perform AutoML.DescribePredictorResponse.Builder autoMLOverrideStrategy(String autoMLOverrideStrategy)
The LatencyOptimized AutoML override strategy is only available in private beta. Contact Amazon
Web Services 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.
autoMLOverrideStrategy -
The LatencyOptimized AutoML override strategy is only available in private beta. Contact
Amazon Web Services 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.
AutoMLOverrideStrategy,
AutoMLOverrideStrategyDescribePredictorResponse.Builder autoMLOverrideStrategy(AutoMLOverrideStrategy autoMLOverrideStrategy)
The LatencyOptimized AutoML override strategy is only available in private beta. Contact Amazon
Web Services 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.
autoMLOverrideStrategy -
The LatencyOptimized AutoML override strategy is only available in private beta. Contact
Amazon Web Services 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.
AutoMLOverrideStrategy,
AutoMLOverrideStrategyDescribePredictorResponse.Builder performHPO(Boolean performHPO)
Whether the predictor is set to perform hyperparameter optimization (HPO).
performHPO - Whether the predictor is set to perform hyperparameter optimization (HPO).DescribePredictorResponse.Builder trainingParameters(Map<String,String> trainingParameters)
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.
trainingParameters - 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.DescribePredictorResponse.Builder evaluationParameters(EvaluationParameters evaluationParameters)
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.
evaluationParameters - 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.default DescribePredictorResponse.Builder evaluationParameters(Consumer<EvaluationParameters.Builder> evaluationParameters)
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.
This is a convenience method that creates an instance of theEvaluationParameters.Builder avoiding
the need to create one manually via EvaluationParameters.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and
its result is passed to evaluationParameters(EvaluationParameters).
evaluationParameters - a consumer that will call methods on EvaluationParameters.BuilderevaluationParameters(EvaluationParameters)DescribePredictorResponse.Builder hpoConfig(HyperParameterTuningJobConfig hpoConfig)
The hyperparameter override values for the algorithm.
hpoConfig - The hyperparameter override values for the algorithm.default DescribePredictorResponse.Builder hpoConfig(Consumer<HyperParameterTuningJobConfig.Builder> hpoConfig)
The hyperparameter override values for the algorithm.
This is a convenience method that creates an instance of theHyperParameterTuningJobConfig.Builder
avoiding the need to create one manually via HyperParameterTuningJobConfig.builder().
When the Consumer completes, SdkBuilder.build() is called
immediately and its result is passed to hpoConfig(HyperParameterTuningJobConfig).
hpoConfig - a consumer that will call methods on HyperParameterTuningJobConfig.BuilderhpoConfig(HyperParameterTuningJobConfig)DescribePredictorResponse.Builder inputDataConfig(InputDataConfig inputDataConfig)
Describes the dataset group that contains the data to use to train the predictor.
inputDataConfig - Describes the dataset group that contains the data to use to train the predictor.default DescribePredictorResponse.Builder inputDataConfig(Consumer<InputDataConfig.Builder> inputDataConfig)
Describes the dataset group that contains the data to use to train the predictor.
This is a convenience method that creates an instance of theInputDataConfig.Builder avoiding the
need to create one manually via InputDataConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to inputDataConfig(InputDataConfig).
inputDataConfig - a consumer that will call methods on InputDataConfig.BuilderinputDataConfig(InputDataConfig)DescribePredictorResponse.Builder featurizationConfig(FeaturizationConfig featurizationConfig)
The featurization configuration.
featurizationConfig - The featurization configuration.default DescribePredictorResponse.Builder featurizationConfig(Consumer<FeaturizationConfig.Builder> featurizationConfig)
The featurization configuration.
This is a convenience method that creates an instance of theFeaturizationConfig.Builder avoiding the
need to create one manually via FeaturizationConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and
its result is passed to featurizationConfig(FeaturizationConfig).
featurizationConfig - a consumer that will call methods on FeaturizationConfig.BuilderfeaturizationConfig(FeaturizationConfig)DescribePredictorResponse.Builder encryptionConfig(EncryptionConfig encryptionConfig)
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
encryptionConfig - An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon
Forecast can assume to access the key.default DescribePredictorResponse.Builder encryptionConfig(Consumer<EncryptionConfig.Builder> encryptionConfig)
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
This is a convenience method that creates an instance of theEncryptionConfig.Builder avoiding the
need to create one manually via EncryptionConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to encryptionConfig(EncryptionConfig).
encryptionConfig - a consumer that will call methods on EncryptionConfig.BuilderencryptionConfig(EncryptionConfig)DescribePredictorResponse.Builder predictorExecutionDetails(PredictorExecutionDetails predictorExecutionDetails)
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.
predictorExecutionDetails - 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.default DescribePredictorResponse.Builder predictorExecutionDetails(Consumer<PredictorExecutionDetails.Builder> predictorExecutionDetails)
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.
This is a convenience method that creates an instance of thePredictorExecutionDetails.Builder
avoiding the need to create one manually via PredictorExecutionDetails.builder().
When the Consumer completes, SdkBuilder.build() is called immediately
and its result is passed to predictorExecutionDetails(PredictorExecutionDetails).
predictorExecutionDetails - a consumer that will call methods on PredictorExecutionDetails.BuilderpredictorExecutionDetails(PredictorExecutionDetails)DescribePredictorResponse.Builder estimatedTimeRemainingInMinutes(Long estimatedTimeRemainingInMinutes)
The estimated time remaining in minutes for the predictor training job to complete.
estimatedTimeRemainingInMinutes - The estimated time remaining in minutes for the predictor training job to complete.DescribePredictorResponse.Builder isAutoPredictor(Boolean isAutoPredictor)
Whether the predictor was created with CreateAutoPredictor.
isAutoPredictor - Whether the predictor was created with CreateAutoPredictor.DescribePredictorResponse.Builder datasetImportJobArns(Collection<String> datasetImportJobArns)
An array of the ARNs of the dataset import jobs used to import training data for the predictor.
datasetImportJobArns - An array of the ARNs of the dataset import jobs used to import training data for the predictor.DescribePredictorResponse.Builder datasetImportJobArns(String... datasetImportJobArns)
An array of the ARNs of the dataset import jobs used to import training data for the predictor.
datasetImportJobArns - An array of the ARNs of the dataset import jobs used to import training data for the predictor.DescribePredictorResponse.Builder status(String status)
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.
status - 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.
DescribePredictorResponse.Builder message(String message)
If an error occurred, an informational message about the error.
message - If an error occurred, an informational message about the error.DescribePredictorResponse.Builder creationTime(Instant creationTime)
When the model training task was created.
creationTime - When the model training task was created.DescribePredictorResponse.Builder lastModificationTime(Instant lastModificationTime)
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.
lastModificationTime - 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.
DescribePredictorResponse.Builder optimizationMetric(String optimizationMetric)
The accuracy metric used to optimize the predictor.
optimizationMetric - The accuracy metric used to optimize the predictor.OptimizationMetric,
OptimizationMetricDescribePredictorResponse.Builder optimizationMetric(OptimizationMetric optimizationMetric)
The accuracy metric used to optimize the predictor.
optimizationMetric - The accuracy metric used to optimize the predictor.OptimizationMetric,
OptimizationMetricCopyright © 2023. All rights reserved.