Interface CreatePredictorRequest.Builder
- All Superinterfaces:
AwsRequest.Builder
,Buildable
,CopyableBuilder<CreatePredictorRequest.Builder,
,CreatePredictorRequest> ForecastRequest.Builder
,SdkBuilder<CreatePredictorRequest.Builder,
,CreatePredictorRequest> SdkPojo
,SdkRequest.Builder
- Enclosing class:
CreatePredictorRequest
-
Method Summary
Modifier and TypeMethodDescriptionalgorithmArn
(String algorithmArn) The Amazon Resource Name (ARN) of the algorithm to use for model training.autoMLOverrideStrategy
(String autoMLOverrideStrategy) autoMLOverrideStrategy
(AutoMLOverrideStrategy autoMLOverrideStrategy) default CreatePredictorRequest.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.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.default CreatePredictorRequest.Builder
evaluationParameters
(Consumer<EvaluationParameters.Builder> evaluationParameters) Used to override the default evaluation parameters of the specified algorithm.evaluationParameters
(EvaluationParameters evaluationParameters) Used to override the default evaluation parameters of the specified algorithm.default CreatePredictorRequest.Builder
featurizationConfig
(Consumer<FeaturizationConfig.Builder> featurizationConfig) The featurization configuration.featurizationConfig
(FeaturizationConfig featurizationConfig) The featurization configuration.forecastHorizon
(Integer forecastHorizon) Specifies the number of time-steps that the model is trained to predict.forecastTypes
(String... forecastTypes) Specifies the forecast types used to train a predictor.forecastTypes
(Collection<String> forecastTypes) Specifies the forecast types used to train a predictor.default CreatePredictorRequest.Builder
hpoConfig
(Consumer<HyperParameterTuningJobConfig.Builder> hpoConfig) Provides hyperparameter override values for the algorithm.hpoConfig
(HyperParameterTuningJobConfig hpoConfig) Provides hyperparameter override values for the algorithm.default CreatePredictorRequest.Builder
inputDataConfig
(Consumer<InputDataConfig.Builder> inputDataConfig) Describes the dataset group that contains the data to use to train the predictor.inputDataConfig
(InputDataConfig inputDataConfig) Describes the dataset group that contains the data to use to train the predictor.optimizationMetric
(String optimizationMetric) The accuracy metric used to optimize the predictor.optimizationMetric
(OptimizationMetric optimizationMetric) The accuracy metric used to optimize the predictor.overrideConfiguration
(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) Add an optional request override configuration.overrideConfiguration
(AwsRequestOverrideConfiguration overrideConfiguration) Add an optional request override configuration.performAutoML
(Boolean performAutoML) Whether to perform AutoML.performHPO
(Boolean performHPO) Whether to perform hyperparameter optimization (HPO).predictorName
(String predictorName) A name for the predictor.tags
(Collection<Tag> tags) The optional metadata that you apply to the predictor to help you categorize and organize them.tags
(Consumer<Tag.Builder>... tags) The optional metadata that you apply to the predictor to help you categorize and organize them.The optional metadata that you apply to the predictor to help you categorize and organize them.trainingParameters
(Map<String, String> trainingParameters) The hyperparameters to override for model training.Methods inherited from interface software.amazon.awssdk.awscore.AwsRequest.Builder
overrideConfiguration
Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copy
Methods inherited from interface software.amazon.awssdk.services.forecast.model.ForecastRequest.Builder
build
Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, build
Methods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFields
-
Method Details
-
predictorName
A name for the predictor.
- Parameters:
predictorName
- A name for the predictor.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
algorithmArn
The Amazon Resource Name (ARN) of the algorithm to use for model training. Required if
PerformAutoML
is not set totrue
.Supported algorithms:
-
arn:aws:forecast:::algorithm/ARIMA
-
arn:aws:forecast:::algorithm/CNN-QR
-
arn:aws:forecast:::algorithm/Deep_AR_Plus
-
arn:aws:forecast:::algorithm/ETS
-
arn:aws:forecast:::algorithm/NPTS
-
arn:aws:forecast:::algorithm/Prophet
- Parameters:
algorithmArn
- The Amazon Resource Name (ARN) of the algorithm to use for model training. Required ifPerformAutoML
is not set totrue
.Supported algorithms:
-
arn:aws:forecast:::algorithm/ARIMA
-
arn:aws:forecast:::algorithm/CNN-QR
-
arn:aws:forecast:::algorithm/Deep_AR_Plus
-
arn:aws:forecast:::algorithm/ETS
-
arn:aws:forecast:::algorithm/NPTS
-
arn:aws:forecast:::algorithm/Prophet
-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
-
forecastHorizon
Specifies the number of time-steps that the model is trained to predict. The forecast horizon is also called the prediction length.
For example, if you configure a dataset for daily data collection (using the
DataFrequency
parameter of the CreateDataset operation) and set the forecast horizon to 10, the model returns predictions for 10 days.The maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.
- Parameters:
forecastHorizon
- Specifies the number of time-steps that the model is trained to predict. The forecast horizon is also called the prediction length.For example, if you configure a dataset for daily data collection (using the
DataFrequency
parameter of the CreateDataset operation) and set the forecast horizon to 10, the model returns predictions for 10 days.The maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
forecastTypes
Specifies the forecast types used to train a predictor. You can specify up to five forecast types. Forecast types can be quantiles from 0.01 to 0.99, by increments of 0.01 or higher. You can also specify the mean forecast with
mean
.The default value is
["0.10", "0.50", "0.9"]
.- Parameters:
forecastTypes
- Specifies the forecast types used to train a predictor. You can specify up to five forecast types. Forecast types can be quantiles from 0.01 to 0.99, by increments of 0.01 or higher. You can also specify the mean forecast withmean
.The default value is
["0.10", "0.50", "0.9"]
.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
forecastTypes
Specifies the forecast types used to train a predictor. You can specify up to five forecast types. Forecast types can be quantiles from 0.01 to 0.99, by increments of 0.01 or higher. You can also specify the mean forecast with
mean
.The default value is
["0.10", "0.50", "0.9"]
.- Parameters:
forecastTypes
- Specifies the forecast types used to train a predictor. You can specify up to five forecast types. Forecast types can be quantiles from 0.01 to 0.99, by increments of 0.01 or higher. You can also specify the mean forecast withmean
.The default value is
["0.10", "0.50", "0.9"]
.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
performAutoML
Whether to perform AutoML. When Amazon Forecast performs AutoML, it evaluates the algorithms it provides and chooses the best algorithm and configuration for your training dataset.
The default value is
false
. In this case, you are required to specify an algorithm.Set
PerformAutoML
totrue
to have Amazon Forecast perform AutoML. This is a good option if you aren't sure which algorithm is suitable for your training data. In this case,PerformHPO
must be false.- Parameters:
performAutoML
- Whether to perform AutoML. When Amazon Forecast performs AutoML, it evaluates the algorithms it provides and chooses the best algorithm and configuration for your training dataset.The default value is
false
. In this case, you are required to specify an algorithm.Set
PerformAutoML
totrue
to have Amazon Forecast perform AutoML. This is a good option if you aren't sure which algorithm is suitable for your training data. In this case,PerformHPO
must be false.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
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.Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use
LatencyOptimized
.This parameter is only valid for predictors trained using AutoML.
- Parameters:
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.Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use
LatencyOptimized
.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
CreatePredictorRequest.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.Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use
LatencyOptimized
.This parameter is only valid for predictors trained using AutoML.
- Parameters:
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.Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use
LatencyOptimized
.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:
-
performHPO
Whether to perform hyperparameter optimization (HPO). HPO finds optimal hyperparameter values for your training data. The process of performing HPO is known as running a hyperparameter tuning job.
The default value is
false
. In this case, Amazon Forecast uses default hyperparameter values from the chosen algorithm.To override the default values, set
PerformHPO
totrue
and, optionally, supply the HyperParameterTuningJobConfig object. The tuning job specifies a metric to optimize, which hyperparameters participate in tuning, and the valid range for each tunable hyperparameter. In this case, you are required to specify an algorithm andPerformAutoML
must be false.The following algorithms support HPO:
-
DeepAR+
-
CNN-QR
- Parameters:
performHPO
- Whether to perform hyperparameter optimization (HPO). HPO finds optimal hyperparameter values for your training data. The process of performing HPO is known as running a hyperparameter tuning job.The default value is
false
. In this case, Amazon Forecast uses default hyperparameter values from the chosen algorithm.To override the default values, set
PerformHPO
totrue
and, optionally, supply the HyperParameterTuningJobConfig object. The tuning job specifies a metric to optimize, which hyperparameters participate in tuning, and the valid range for each tunable hyperparameter. In this case, you are required to specify an algorithm andPerformAutoML
must be false.The following algorithms support HPO:
-
DeepAR+
-
CNN-QR
-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
-
trainingParameters
The hyperparameters to override for model training. The hyperparameters that you can override are listed in the individual algorithms. For the list of supported algorithms, see aws-forecast-choosing-recipes.
- Parameters:
trainingParameters
- The hyperparameters to override for model training. The hyperparameters that you can override are listed in the individual algorithms. For the list of supported algorithms, see aws-forecast-choosing-recipes.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
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.
-
evaluationParameters
default CreatePredictorRequest.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 viaEvaluationParameters.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toevaluationParameters(EvaluationParameters)
.- Parameters:
evaluationParameters
- a consumer that will call methods onEvaluationParameters.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
hpoConfig
Provides hyperparameter override values for the algorithm. If you don't provide this parameter, Amazon Forecast uses default values. The individual algorithms specify which hyperparameters support hyperparameter optimization (HPO). For more information, see aws-forecast-choosing-recipes.
If you included the
HPOConfig
object, you must setPerformHPO
to true.- Parameters:
hpoConfig
- Provides hyperparameter override values for the algorithm. If you don't provide this parameter, Amazon Forecast uses default values. The individual algorithms specify which hyperparameters support hyperparameter optimization (HPO). For more information, see aws-forecast-choosing-recipes.If you included the
HPOConfig
object, you must setPerformHPO
to true.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
hpoConfig
default CreatePredictorRequest.Builder hpoConfig(Consumer<HyperParameterTuningJobConfig.Builder> hpoConfig) Provides hyperparameter override values for the algorithm. If you don't provide this parameter, Amazon Forecast uses default values. The individual algorithms specify which hyperparameters support hyperparameter optimization (HPO). For more information, see aws-forecast-choosing-recipes.
If you included the
This is a convenience method that creates an instance of theHPOConfig
object, you must setPerformHPO
to true.HyperParameterTuningJobConfig.Builder
avoiding the need to create one manually viaHyperParameterTuningJobConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tohpoConfig(HyperParameterTuningJobConfig)
.- Parameters:
hpoConfig
- a consumer that will call methods onHyperParameterTuningJobConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
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.
-
inputDataConfig
default CreatePredictorRequest.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 viaInputDataConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toinputDataConfig(InputDataConfig)
.- Parameters:
inputDataConfig
- a consumer that will call methods onInputDataConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
featurizationConfig
The featurization configuration.
- Parameters:
featurizationConfig
- The featurization configuration.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
featurizationConfig
default CreatePredictorRequest.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 viaFeaturizationConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tofeaturizationConfig(FeaturizationConfig)
.- Parameters:
featurizationConfig
- a consumer that will call methods onFeaturizationConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
encryptionConfig
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
- Parameters:
encryptionConfig
- An Key Management Service (KMS) key and the 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.
-
encryptionConfig
default CreatePredictorRequest.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 viaEncryptionConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toencryptionConfig(EncryptionConfig)
.- Parameters:
encryptionConfig
- a consumer that will call methods onEncryptionConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
tags
The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.
The following basic restrictions apply to tags:
-
Maximum number of tags per resource - 50.
-
For each resource, each tag key must be unique, and each tag key can have only one value.
-
Maximum key length - 128 Unicode characters in UTF-8.
-
Maximum value length - 256 Unicode characters in UTF-8.
-
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
-
Tag keys and values are case sensitive.
-
Do not use
aws:
,AWS:
, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value hasaws
as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix ofaws
do not count against your tags per resource limit.
- Parameters:
tags
- The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.The following basic restrictions apply to tags:
-
Maximum number of tags per resource - 50.
-
For each resource, each tag key must be unique, and each tag key can have only one value.
-
Maximum key length - 128 Unicode characters in UTF-8.
-
Maximum value length - 256 Unicode characters in UTF-8.
-
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
-
Tag keys and values are case sensitive.
-
Do not use
aws:
,AWS:
, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value hasaws
as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix ofaws
do not count against your tags per resource limit.
-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
-
tags
The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.
The following basic restrictions apply to tags:
-
Maximum number of tags per resource - 50.
-
For each resource, each tag key must be unique, and each tag key can have only one value.
-
Maximum key length - 128 Unicode characters in UTF-8.
-
Maximum value length - 256 Unicode characters in UTF-8.
-
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
-
Tag keys and values are case sensitive.
-
Do not use
aws:
,AWS:
, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value hasaws
as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix ofaws
do not count against your tags per resource limit.
- Parameters:
tags
- The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.The following basic restrictions apply to tags:
-
Maximum number of tags per resource - 50.
-
For each resource, each tag key must be unique, and each tag key can have only one value.
-
Maximum key length - 128 Unicode characters in UTF-8.
-
Maximum value length - 256 Unicode characters in UTF-8.
-
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
-
Tag keys and values are case sensitive.
-
Do not use
aws:
,AWS:
, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value hasaws
as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix ofaws
do not count against your tags per resource limit.
-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
-
tags
The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.
The following basic restrictions apply to tags:
-
Maximum number of tags per resource - 50.
-
For each resource, each tag key must be unique, and each tag key can have only one value.
-
Maximum key length - 128 Unicode characters in UTF-8.
-
Maximum value length - 256 Unicode characters in UTF-8.
-
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
-
Tag keys and values are case sensitive.
-
Do not use
aws:
,AWS:
, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value hasaws
as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix ofaws
do not count against your tags per resource limit.
Tag.Builder
avoiding the need to create one manually viaTag.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed totags(List<Tag>)
.- Parameters:
tags
- a consumer that will call methods onTag.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
-
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
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:
-
overrideConfiguration
CreatePredictorRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) Description copied from interface:AwsRequest.Builder
Add an optional request override configuration.- Specified by:
overrideConfiguration
in interfaceAwsRequest.Builder
- Parameters:
overrideConfiguration
- The override configuration.- Returns:
- This object for method chaining.
-
overrideConfiguration
CreatePredictorRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) Description copied from interface:AwsRequest.Builder
Add an optional request override configuration.- Specified by:
overrideConfiguration
in interfaceAwsRequest.Builder
- Parameters:
builderConsumer
- AConsumer
to which an emptyAwsRequestOverrideConfiguration.Builder
will be given.- Returns:
- This object for method chaining.
-