DescribePredictorResult (AWS SDK for Java

java.lang.Object
- com.amazonaws.AmazonWebServiceResult<ResponseMetadata>
- - com.amazonaws.services.forecast.model.DescribePredictorResult

All Implemented Interfaces:: Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class DescribePredictorResult
extends AmazonWebServiceResult<ResponseMetadata>
implements Serializable, Cloneable

See Also:: AWS API Documentation, Serialized Form

Constructor Summary

Constructors
Constructor and Description

DescribePredictorResult()

Constructors
Constructor and Description
`DescribePredictorResult()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`DescribePredictorResult`	`addTrainingParametersEntry(String key, String value)` Add a single TrainingParameters entry
`DescribePredictorResult`	`clearTrainingParametersEntries()` Removes all the entries added into TrainingParameters.
`DescribePredictorResult`	`clone()`
`boolean`	`equals(Object obj)`
`String`	`getAlgorithmArn()` The Amazon Resource Name (ARN) of the algorithm used for model training.
`List<String>`	`getAutoMLAlgorithmArns()` When `PerformAutoML` is specified, the ARN of the chosen algorithm.
`String`	`getAutoMLOverrideStrategy()`
`Date`	`getCreationTime()` When the model training task was created.
`List<String>`	`getDatasetImportJobArns()` An array of the ARNs of the dataset import jobs used to import training data for the predictor.
`EncryptionConfig`	`getEncryptionConfig()` 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.
`Long`	`getEstimatedTimeRemainingInMinutes()` The estimated time remaining in minutes for the predictor training job to complete.
`EvaluationParameters`	`getEvaluationParameters()` Used to override the default evaluation parameters of the specified algorithm.
`FeaturizationConfig`	`getFeaturizationConfig()` The featurization configuration.
`Integer`	`getForecastHorizon()` The number of time-steps of the forecast.
`List<String>`	`getForecastTypes()` The forecast types used during predictor training.
`HyperParameterTuningJobConfig`	`getHPOConfig()` The hyperparameter override values for the algorithm.
`InputDataConfig`	`getInputDataConfig()` Describes the dataset group that contains the data to use to train the predictor.
`Boolean`	`getIsAutoPredictor()` Whether the predictor was created with CreateAutoPredictor.
`Date`	`getLastModificationTime()` The last time the resource was modified.
`String`	`getMessage()` If an error occurred, an informational message about the error.
`String`	`getOptimizationMetric()` The accuracy metric used to optimize the predictor.
`Boolean`	`getPerformAutoML()` Whether the predictor is set to perform AutoML.
`Boolean`	`getPerformHPO()` Whether the predictor is set to perform hyperparameter optimization (HPO).
`String`	`getPredictorArn()` The ARN of the predictor.
`PredictorExecutionDetails`	`getPredictorExecutionDetails()` Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor.
`String`	`getPredictorName()` The name of the predictor.
`String`	`getStatus()` The status of the predictor.
`Map<String,String>`	`getTrainingParameters()` The default training parameters or overrides selected during model training.
`int`	`hashCode()`
`Boolean`	`isAutoPredictor()` Whether the predictor was created with CreateAutoPredictor.
`Boolean`	`isPerformAutoML()` Whether the predictor is set to perform AutoML.
`Boolean`	`isPerformHPO()` Whether the predictor is set to perform hyperparameter optimization (HPO).
`void`	`setAlgorithmArn(String algorithmArn)` The Amazon Resource Name (ARN) of the algorithm used for model training.
`void`	`setAutoMLAlgorithmArns(Collection<String> autoMLAlgorithmArns)` When `PerformAutoML` is specified, the ARN of the chosen algorithm.
`void`	`setAutoMLOverrideStrategy(String autoMLOverrideStrategy)`
`void`	`setCreationTime(Date creationTime)` When the model training task was created.
`void`	`setDatasetImportJobArns(Collection<String> datasetImportJobArns)` An array of the ARNs of the dataset import jobs used to import training data for the predictor.
`void`	`setEncryptionConfig(EncryptionConfig encryptionConfig)` 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.
`void`	`setEstimatedTimeRemainingInMinutes(Long estimatedTimeRemainingInMinutes)` The estimated time remaining in minutes for the predictor training job to complete.
`void`	`setEvaluationParameters(EvaluationParameters evaluationParameters)` Used to override the default evaluation parameters of the specified algorithm.
`void`	`setFeaturizationConfig(FeaturizationConfig featurizationConfig)` The featurization configuration.
`void`	`setForecastHorizon(Integer forecastHorizon)` The number of time-steps of the forecast.
`void`	`setForecastTypes(Collection<String> forecastTypes)` The forecast types used during predictor training.
`void`	`setHPOConfig(HyperParameterTuningJobConfig hPOConfig)` The hyperparameter override values for the algorithm.
`void`	`setInputDataConfig(InputDataConfig inputDataConfig)` Describes the dataset group that contains the data to use to train the predictor.
`void`	`setIsAutoPredictor(Boolean isAutoPredictor)` Whether the predictor was created with CreateAutoPredictor.
`void`	`setLastModificationTime(Date lastModificationTime)` The last time the resource was modified.
`void`	`setMessage(String message)` If an error occurred, an informational message about the error.
`void`	`setOptimizationMetric(String optimizationMetric)` The accuracy metric used to optimize the predictor.
`void`	`setPerformAutoML(Boolean performAutoML)` Whether the predictor is set to perform AutoML.
`void`	`setPerformHPO(Boolean performHPO)` Whether the predictor is set to perform hyperparameter optimization (HPO).
`void`	`setPredictorArn(String predictorArn)` The ARN of the predictor.
`void`	`setPredictorExecutionDetails(PredictorExecutionDetails predictorExecutionDetails)` Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor.
`void`	`setPredictorName(String predictorName)` The name of the predictor.
`void`	`setStatus(String status)` The status of the predictor.
`void`	`setTrainingParameters(Map<String,String> trainingParameters)` The default training parameters or overrides selected during model training.
`String`	`toString()` Returns a string representation of this object.
`DescribePredictorResult`	`withAlgorithmArn(String algorithmArn)` The Amazon Resource Name (ARN) of the algorithm used for model training.
`DescribePredictorResult`	`withAutoMLAlgorithmArns(Collection<String> autoMLAlgorithmArns)` When `PerformAutoML` is specified, the ARN of the chosen algorithm.
`DescribePredictorResult`	`withAutoMLAlgorithmArns(String... autoMLAlgorithmArns)` When `PerformAutoML` is specified, the ARN of the chosen algorithm.
`DescribePredictorResult`	`withAutoMLOverrideStrategy(AutoMLOverrideStrategy autoMLOverrideStrategy)`
`DescribePredictorResult`	`withAutoMLOverrideStrategy(String autoMLOverrideStrategy)`
`DescribePredictorResult`	`withCreationTime(Date creationTime)` When the model training task was created.
`DescribePredictorResult`	`withDatasetImportJobArns(Collection<String> datasetImportJobArns)` An array of the ARNs of the dataset import jobs used to import training data for the predictor.
`DescribePredictorResult`	`withDatasetImportJobArns(String... datasetImportJobArns)` An array of the ARNs of the dataset import jobs used to import training data for the predictor.
`DescribePredictorResult`	`withEncryptionConfig(EncryptionConfig encryptionConfig)` 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.
`DescribePredictorResult`	`withEstimatedTimeRemainingInMinutes(Long estimatedTimeRemainingInMinutes)` The estimated time remaining in minutes for the predictor training job to complete.
`DescribePredictorResult`	`withEvaluationParameters(EvaluationParameters evaluationParameters)` Used to override the default evaluation parameters of the specified algorithm.
`DescribePredictorResult`	`withFeaturizationConfig(FeaturizationConfig featurizationConfig)` The featurization configuration.
`DescribePredictorResult`	`withForecastHorizon(Integer forecastHorizon)` The number of time-steps of the forecast.
`DescribePredictorResult`	`withForecastTypes(Collection<String> forecastTypes)` The forecast types used during predictor training.
`DescribePredictorResult`	`withForecastTypes(String... forecastTypes)` The forecast types used during predictor training.
`DescribePredictorResult`	`withHPOConfig(HyperParameterTuningJobConfig hPOConfig)` The hyperparameter override values for the algorithm.
`DescribePredictorResult`	`withInputDataConfig(InputDataConfig inputDataConfig)` Describes the dataset group that contains the data to use to train the predictor.
`DescribePredictorResult`	`withIsAutoPredictor(Boolean isAutoPredictor)` Whether the predictor was created with CreateAutoPredictor.
`DescribePredictorResult`	`withLastModificationTime(Date lastModificationTime)` The last time the resource was modified.
`DescribePredictorResult`	`withMessage(String message)` If an error occurred, an informational message about the error.
`DescribePredictorResult`	`withOptimizationMetric(OptimizationMetric optimizationMetric)` The accuracy metric used to optimize the predictor.
`DescribePredictorResult`	`withOptimizationMetric(String optimizationMetric)` The accuracy metric used to optimize the predictor.
`DescribePredictorResult`	`withPerformAutoML(Boolean performAutoML)` Whether the predictor is set to perform AutoML.
`DescribePredictorResult`	`withPerformHPO(Boolean performHPO)` Whether the predictor is set to perform hyperparameter optimization (HPO).
`DescribePredictorResult`	`withPredictorArn(String predictorArn)` The ARN of the predictor.
`DescribePredictorResult`	`withPredictorExecutionDetails(PredictorExecutionDetails predictorExecutionDetails)` Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor.
`DescribePredictorResult`	`withPredictorName(String predictorName)` The name of the predictor.
`DescribePredictorResult`	`withStatus(String status)` The status of the predictor.
`DescribePredictorResult`	`withTrainingParameters(Map<String,String> trainingParameters)` The default training parameters or overrides selected during model training.

Methods inherited from class com.amazonaws.AmazonWebServiceResult
getSdkHttpMetadata, getSdkResponseMetadata, setSdkHttpMetadata, setSdkResponseMetadata

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - DescribePredictorResult
```
public DescribePredictorResult()
```
- Method Detail
  - setPredictorArn
```
public void setPredictorArn(String predictorArn)
```
    The ARN of the predictor.
    
    Parameters:
    
    predictorArn - The ARN of the predictor.
  - getPredictorArn
```
public String getPredictorArn()
```
    The ARN of the predictor.
    
    Returns:
    
    The ARN of the predictor.
  - withPredictorArn
```
public DescribePredictorResult withPredictorArn(String predictorArn)
```
    The ARN of the predictor.
    
    Parameters:
    
    predictorArn - The ARN of the predictor.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setPredictorName
```
public void setPredictorName(String predictorName)
```
    The name of the predictor.
    
    Parameters:
    
    predictorName - The name of the predictor.
  - getPredictorName
```
public String getPredictorName()
```
    The name of the predictor.
    
    Returns:
    
    The name of the predictor.
  - withPredictorName
```
public DescribePredictorResult withPredictorName(String predictorName)
```
    The name of the predictor.
    
    Parameters:
    
    predictorName - The name of the predictor.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setAlgorithmArn
```
public void setAlgorithmArn(String algorithmArn)
```
    The Amazon Resource Name (ARN) of the algorithm used for model training.
    
    Parameters:
    
    algorithmArn - The Amazon Resource Name (ARN) of the algorithm used for model training.
  - getAlgorithmArn
```
public String getAlgorithmArn()
```
    The Amazon Resource Name (ARN) of the algorithm used for model training.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the algorithm used for model training.
  - withAlgorithmArn
```
public DescribePredictorResult withAlgorithmArn(String algorithmArn)
```
    The Amazon Resource Name (ARN) of the algorithm used for model training.
    
    Parameters:
    
    algorithmArn - The Amazon Resource Name (ARN) of the algorithm used for model training.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getAutoMLAlgorithmArns
```
public List<String> getAutoMLAlgorithmArns()
```
    When PerformAutoML is specified, the ARN of the chosen algorithm.
    
    Returns:
    
    When PerformAutoML is specified, the ARN of the chosen algorithm.
  - setAutoMLAlgorithmArns
```
public void setAutoMLAlgorithmArns(Collection<String> autoMLAlgorithmArns)
```
    When PerformAutoML is specified, the ARN of the chosen algorithm.
    
    Parameters:
    
    autoMLAlgorithmArns - When PerformAutoML is specified, the ARN of the chosen algorithm.
  - withAutoMLAlgorithmArns
```
public DescribePredictorResult withAutoMLAlgorithmArns(String... autoMLAlgorithmArns)
```
    When PerformAutoML is specified, the ARN of the chosen algorithm.
    
    NOTE: This method appends the values to the existing list (if any). Use setAutoMLAlgorithmArns(java.util.Collection) or withAutoMLAlgorithmArns(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    autoMLAlgorithmArns - When PerformAutoML is specified, the ARN of the chosen algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withAutoMLAlgorithmArns
```
public DescribePredictorResult withAutoMLAlgorithmArns(Collection<String> autoMLAlgorithmArns)
```
    When PerformAutoML is specified, the ARN of the chosen algorithm.
    
    Parameters:
    
    autoMLAlgorithmArns - When PerformAutoML is specified, the ARN of the chosen algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setForecastHorizon
```
public void setForecastHorizon(Integer forecastHorizon)
```
    The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
    
    Parameters:
    
    forecastHorizon - The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
  - getForecastHorizon
```
public Integer getForecastHorizon()
```
    The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
    
    Returns:
    
    The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
  - withForecastHorizon
```
public DescribePredictorResult withForecastHorizon(Integer forecastHorizon)
```
    The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
    
    Parameters:
    
    forecastHorizon - The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getForecastTypes
```
public List<String> getForecastTypes()
```
    The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
    
    Returns:
    
    The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
  - setForecastTypes
```
public void setForecastTypes(Collection<String> forecastTypes)
```
    The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
    
    Parameters:
    
    forecastTypes - The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
  - withForecastTypes
```
public DescribePredictorResult withForecastTypes(String... forecastTypes)
```
    The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
    
    NOTE: This method appends the values to the existing list (if any). Use setForecastTypes(java.util.Collection) or withForecastTypes(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    forecastTypes - The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withForecastTypes
```
public DescribePredictorResult withForecastTypes(Collection<String> forecastTypes)
```
    The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
    
    Parameters:
    
    forecastTypes - The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setPerformAutoML
```
public void setPerformAutoML(Boolean performAutoML)
```
    Whether the predictor is set to perform AutoML.
    
    Parameters:
    
    performAutoML - Whether the predictor is set to perform AutoML.
  - getPerformAutoML
```
public Boolean getPerformAutoML()
```
    Whether the predictor is set to perform AutoML.
    
    Returns:
    
    Whether the predictor is set to perform AutoML.
  - withPerformAutoML
```
public DescribePredictorResult withPerformAutoML(Boolean performAutoML)
```
    Whether the predictor is set to perform AutoML.
    
    Parameters:
    
    performAutoML - Whether the predictor is set to perform AutoML.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - isPerformAutoML
```
public Boolean isPerformAutoML()
```
    Whether the predictor is set to perform AutoML.
    
    Returns:
    
    Whether the predictor is set to perform AutoML.
  - setAutoMLOverrideStrategy
```
public void setAutoMLOverrideStrategy(String autoMLOverrideStrategy)
```
    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.
    
    Parameters:
    
    autoMLOverrideStrategy -
    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.
    
    See Also:
    
    AutoMLOverrideStrategy
  - getAutoMLOverrideStrategy
```
public String getAutoMLOverrideStrategy()
```
    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.
    
    Returns:
    
    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.
    
    See Also:
    
    AutoMLOverrideStrategy
  - withAutoMLOverrideStrategy
```
public DescribePredictorResult withAutoMLOverrideStrategy(String autoMLOverrideStrategy)
```
    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.
    
    Parameters:
    
    autoMLOverrideStrategy -
    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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    AutoMLOverrideStrategy
  - withAutoMLOverrideStrategy
```
public DescribePredictorResult withAutoMLOverrideStrategy(AutoMLOverrideStrategy autoMLOverrideStrategy)
```
    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.
    
    Parameters:
    
    autoMLOverrideStrategy -
    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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    AutoMLOverrideStrategy
  - setPerformHPO
```
public void setPerformHPO(Boolean performHPO)
```
    Whether the predictor is set to perform hyperparameter optimization (HPO).
    
    Parameters:
    
    performHPO - Whether the predictor is set to perform hyperparameter optimization (HPO).
  - getPerformHPO
```
public Boolean getPerformHPO()
```
    Whether the predictor is set to perform hyperparameter optimization (HPO).
    
    Returns:
    
    Whether the predictor is set to perform hyperparameter optimization (HPO).
  - withPerformHPO
```
public DescribePredictorResult withPerformHPO(Boolean performHPO)
```
    Whether the predictor is set to perform hyperparameter optimization (HPO).
    
    Parameters:
    
    performHPO - Whether the predictor is set to perform hyperparameter optimization (HPO).
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - isPerformHPO
```
public Boolean isPerformHPO()
```
    Whether the predictor is set to perform hyperparameter optimization (HPO).
    
    Returns:
    
    Whether the predictor is set to perform hyperparameter optimization (HPO).
  - getTrainingParameters
```
public Map<String,String> getTrainingParameters()
```
    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.
    
    Returns:
    
    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.
  - setTrainingParameters
```
public void setTrainingParameters(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.
    
    Parameters:
    
    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.
  - withTrainingParameters
```
public DescribePredictorResult withTrainingParameters(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.
    
    Parameters:
    
    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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - addTrainingParametersEntry
```
public DescribePredictorResult addTrainingParametersEntry(String key,
                                                          String value)
```
    Add a single TrainingParameters entry
    
    See Also:
    
    withTrainingParameters(java.util.Map<java.lang.String, java.lang.String>)
  - clearTrainingParametersEntries
```
public DescribePredictorResult clearTrainingParametersEntries()
```
    Removes all the entries added into TrainingParameters.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setEvaluationParameters
```
public void setEvaluationParameters(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.
    
    Parameters:
    
    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.
  - getEvaluationParameters
```
public EvaluationParameters getEvaluationParameters()
```
    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.
    
    Returns:
    
    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.
  - withEvaluationParameters
```
public DescribePredictorResult withEvaluationParameters(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.
    
    Parameters:
    
    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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setHPOConfig
```
public void setHPOConfig(HyperParameterTuningJobConfig hPOConfig)
```
    The hyperparameter override values for the algorithm.
    
    Parameters:
    
    hPOConfig - The hyperparameter override values for the algorithm.
  - getHPOConfig
```
public HyperParameterTuningJobConfig getHPOConfig()
```
    The hyperparameter override values for the algorithm.
    
    Returns:
    
    The hyperparameter override values for the algorithm.
  - withHPOConfig
```
public DescribePredictorResult withHPOConfig(HyperParameterTuningJobConfig hPOConfig)
```
    The hyperparameter override values for the algorithm.
    
    Parameters:
    
    hPOConfig - The hyperparameter override values for the algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setInputDataConfig
```
public void setInputDataConfig(InputDataConfig inputDataConfig)
```
    Describes the dataset group that contains the data to use to train the predictor.
    
    Parameters:
    
    inputDataConfig - Describes the dataset group that contains the data to use to train the predictor.
  - getInputDataConfig
```
public InputDataConfig getInputDataConfig()
```
    Describes the dataset group that contains the data to use to train the predictor.
    
    Returns:
    
    Describes the dataset group that contains the data to use to train the predictor.
  - withInputDataConfig
```
public DescribePredictorResult withInputDataConfig(InputDataConfig inputDataConfig)
```
    Describes the dataset group that contains the data to use to train the predictor.
    
    Parameters:
    
    inputDataConfig - Describes the dataset group that contains the data to use to train the predictor.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setFeaturizationConfig
```
public void setFeaturizationConfig(FeaturizationConfig featurizationConfig)
```
    The featurization configuration.
    
    Parameters:
    
    featurizationConfig - The featurization configuration.
  - getFeaturizationConfig
```
public FeaturizationConfig getFeaturizationConfig()
```
    The featurization configuration.
    
    Returns:
    
    The featurization configuration.
  - withFeaturizationConfig
```
public DescribePredictorResult withFeaturizationConfig(FeaturizationConfig featurizationConfig)
```
    The featurization configuration.
    
    Parameters:
    
    featurizationConfig - The featurization configuration.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setEncryptionConfig
```
public void setEncryptionConfig(EncryptionConfig encryptionConfig)
```
    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.
    
    Parameters:
    
    encryptionConfig - 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.
  - getEncryptionConfig
```
public EncryptionConfig getEncryptionConfig()
```
    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.
    
    Returns:
    
    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.
  - withEncryptionConfig
```
public DescribePredictorResult withEncryptionConfig(EncryptionConfig encryptionConfig)
```
    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.
    
    Parameters:
    
    encryptionConfig - 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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setPredictorExecutionDetails
```
public void setPredictorExecutionDetails(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.
    
    Parameters:
    
    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.
  - getPredictorExecutionDetails
```
public PredictorExecutionDetails getPredictorExecutionDetails()
```
    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.
    
    Returns:
    
    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.
  - withPredictorExecutionDetails
```
public DescribePredictorResult withPredictorExecutionDetails(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.
    
    Parameters:
    
    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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setEstimatedTimeRemainingInMinutes
```
public void setEstimatedTimeRemainingInMinutes(Long estimatedTimeRemainingInMinutes)
```
    The estimated time remaining in minutes for the predictor training job to complete.
    
    Parameters:
    
    estimatedTimeRemainingInMinutes - The estimated time remaining in minutes for the predictor training job to complete.
  - getEstimatedTimeRemainingInMinutes
```
public Long getEstimatedTimeRemainingInMinutes()
```
    The estimated time remaining in minutes for the predictor training job to complete.
    
    Returns:
    
    The estimated time remaining in minutes for the predictor training job to complete.
  - withEstimatedTimeRemainingInMinutes
```
public DescribePredictorResult withEstimatedTimeRemainingInMinutes(Long estimatedTimeRemainingInMinutes)
```
    The estimated time remaining in minutes for the predictor training job to complete.
    
    Parameters:
    
    estimatedTimeRemainingInMinutes - The estimated time remaining in minutes for the predictor training job to complete.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setIsAutoPredictor
```
public void setIsAutoPredictor(Boolean isAutoPredictor)
```
    Whether the predictor was created with CreateAutoPredictor.
    
    Parameters:
    
    isAutoPredictor - Whether the predictor was created with CreateAutoPredictor.
  - getIsAutoPredictor
```
public Boolean getIsAutoPredictor()
```
    Whether the predictor was created with CreateAutoPredictor.
    
    Returns:
    
    Whether the predictor was created with CreateAutoPredictor.
  - withIsAutoPredictor
```
public DescribePredictorResult withIsAutoPredictor(Boolean isAutoPredictor)
```
    Whether the predictor was created with CreateAutoPredictor.
    
    Parameters:
    
    isAutoPredictor - Whether the predictor was created with CreateAutoPredictor.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - isAutoPredictor
```
public Boolean isAutoPredictor()
```
    Whether the predictor was created with CreateAutoPredictor.
    
    Returns:
    
    Whether the predictor was created with CreateAutoPredictor.
  - getDatasetImportJobArns
```
public List<String> getDatasetImportJobArns()
```
    An array of the ARNs of the dataset import jobs used to import training data for the predictor.
    
    Returns:
    
    An array of the ARNs of the dataset import jobs used to import training data for the predictor.
  - setDatasetImportJobArns
```
public void setDatasetImportJobArns(Collection<String> datasetImportJobArns)
```
    An array of the ARNs of the dataset import jobs used to import training data for the predictor.
    
    Parameters:
    
    datasetImportJobArns - An array of the ARNs of the dataset import jobs used to import training data for the predictor.
  - withDatasetImportJobArns
```
public DescribePredictorResult withDatasetImportJobArns(String... datasetImportJobArns)
```
    An array of the ARNs of the dataset import jobs used to import training data for the predictor.
    
    NOTE: This method appends the values to the existing list (if any). Use setDatasetImportJobArns(java.util.Collection) or withDatasetImportJobArns(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    datasetImportJobArns - An array of the ARNs of the dataset import jobs used to import training data for the predictor.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withDatasetImportJobArns
```
public DescribePredictorResult withDatasetImportJobArns(Collection<String> datasetImportJobArns)
```
    An array of the ARNs of the dataset import jobs used to import training data for the predictor.
    
    Parameters:
    
    datasetImportJobArns - An array of the ARNs of the dataset import jobs used to import training data for the predictor.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setStatus
```
public void setStatus(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.
    Parameters:
    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.
  - getStatus
```
public String getStatus()
```
    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.
    Returns:
    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.
  - withStatus
```
public DescribePredictorResult withStatus(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.
    Parameters:
    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.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setMessage
```
public void setMessage(String message)
```
    If an error occurred, an informational message about the error.
    
    Parameters:
    
    message - If an error occurred, an informational message about the error.
  - getMessage
```
public String getMessage()
```
    If an error occurred, an informational message about the error.
    
    Returns:
    
    If an error occurred, an informational message about the error.
  - withMessage
```
public DescribePredictorResult withMessage(String message)
```
    If an error occurred, an informational message about the error.
    
    Parameters:
    
    message - If an error occurred, an informational message about the error.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setCreationTime
```
public void setCreationTime(Date creationTime)
```
    When the model training task was created.
    
    Parameters:
    
    creationTime - When the model training task was created.
  - getCreationTime
```
public Date getCreationTime()
```
    When the model training task was created.
    
    Returns:
    
    When the model training task was created.
  - withCreationTime
```
public DescribePredictorResult withCreationTime(Date creationTime)
```
    When the model training task was created.
    
    Parameters:
    
    creationTime - When the model training task was created.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLastModificationTime
```
public void setLastModificationTime(Date 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.
    Parameters:
    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.
  - getLastModificationTime
```
public Date getLastModificationTime()
```
    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.
    Returns:
    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.
  - withLastModificationTime
```
public DescribePredictorResult withLastModificationTime(Date 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.
    Parameters:
    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.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setOptimizationMetric
```
public void setOptimizationMetric(String optimizationMetric)
```
    The accuracy metric used to optimize the predictor.
    
    Parameters:
    
    optimizationMetric - The accuracy metric used to optimize the predictor.
    
    See Also:
    
    OptimizationMetric
  - getOptimizationMetric
```
public String getOptimizationMetric()
```
    The accuracy metric used to optimize the predictor.
    
    Returns:
    
    The accuracy metric used to optimize the predictor.
    
    See Also:
    
    OptimizationMetric
  - withOptimizationMetric
```
public DescribePredictorResult withOptimizationMetric(String optimizationMetric)
```
    The accuracy metric used to optimize the predictor.
    
    Parameters:
    
    optimizationMetric - The accuracy metric used to optimize the predictor.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    OptimizationMetric
  - withOptimizationMetric
```
public DescribePredictorResult withOptimizationMetric(OptimizationMetric optimizationMetric)
```
    The accuracy metric used to optimize the predictor.
    
    Parameters:
    
    optimizationMetric - The accuracy metric used to optimize the predictor.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    OptimizationMetric
  - toString
```
public String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    A string representation of this object.
    
    See Also:
    
    Object.toString()
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - clone
```
public DescribePredictorResult clone()
```
    Overrides:
    
    clone in class Object

Did this page help you?

Class DescribePredictorResult

Constructor Summary

Method Summary

Methods inherited from class com.amazonaws.AmazonWebServiceResult

Methods inherited from class java.lang.Object

Constructor Detail

DescribePredictorResult

Method Detail

setPredictorArn

getPredictorArn

withPredictorArn

setPredictorName

getPredictorName

withPredictorName

setAlgorithmArn

getAlgorithmArn

withAlgorithmArn

getAutoMLAlgorithmArns

setAutoMLAlgorithmArns

withAutoMLAlgorithmArns

withAutoMLAlgorithmArns

setForecastHorizon

getForecastHorizon

withForecastHorizon

getForecastTypes

setForecastTypes

withForecastTypes

withForecastTypes

setPerformAutoML

getPerformAutoML

withPerformAutoML

isPerformAutoML

setAutoMLOverrideStrategy

getAutoMLOverrideStrategy

withAutoMLOverrideStrategy

withAutoMLOverrideStrategy

setPerformHPO

getPerformHPO

withPerformHPO

isPerformHPO

getTrainingParameters

setTrainingParameters

withTrainingParameters

addTrainingParametersEntry

clearTrainingParametersEntries

setEvaluationParameters

getEvaluationParameters

withEvaluationParameters

setHPOConfig

getHPOConfig

withHPOConfig

setInputDataConfig

getInputDataConfig

withInputDataConfig

setFeaturizationConfig

getFeaturizationConfig

withFeaturizationConfig

setEncryptionConfig

getEncryptionConfig

withEncryptionConfig

setPredictorExecutionDetails

getPredictorExecutionDetails

withPredictorExecutionDetails

setEstimatedTimeRemainingInMinutes

getEstimatedTimeRemainingInMinutes

withEstimatedTimeRemainingInMinutes

setIsAutoPredictor

getIsAutoPredictor

withIsAutoPredictor

isAutoPredictor

getDatasetImportJobArns

setDatasetImportJobArns

withDatasetImportJobArns

withDatasetImportJobArns

setStatus

getStatus

withStatus

setMessage

getMessage