public static interface CreatePredictorRequest.Builder extends ForecastRequest.Builder, SdkPojo, CopyableBuilder<CreatePredictorRequest.Builder,CreatePredictorRequest>
| Modifier and Type | Method and Description |
|---|---|
CreatePredictorRequest.Builder |
algorithmArn(String algorithmArn)
The Amazon Resource Name (ARN) of the algorithm to use for model training.
|
CreatePredictorRequest.Builder |
autoMLOverrideStrategy(AutoMLOverrideStrategy autoMLOverrideStrategy)
|
CreatePredictorRequest.Builder |
autoMLOverrideStrategy(String 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.
|
CreatePredictorRequest.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.
|
default CreatePredictorRequest.Builder |
evaluationParameters(Consumer<EvaluationParameters.Builder> evaluationParameters)
Used to override the default evaluation parameters of the specified algorithm.
|
CreatePredictorRequest.Builder |
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.
|
CreatePredictorRequest.Builder |
featurizationConfig(FeaturizationConfig featurizationConfig)
The featurization configuration.
|
CreatePredictorRequest.Builder |
forecastHorizon(Integer forecastHorizon)
Specifies the number of time-steps that the model is trained to predict.
|
CreatePredictorRequest.Builder |
forecastTypes(Collection<String> forecastTypes)
Specifies the forecast types used to train a predictor.
|
CreatePredictorRequest.Builder |
forecastTypes(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.
|
CreatePredictorRequest.Builder |
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.
|
CreatePredictorRequest.Builder |
inputDataConfig(InputDataConfig inputDataConfig)
Describes the dataset group that contains the data to use to train the predictor.
|
CreatePredictorRequest.Builder |
optimizationMetric(OptimizationMetric optimizationMetric)
The accuracy metric used to optimize the predictor.
|
CreatePredictorRequest.Builder |
optimizationMetric(String optimizationMetric)
The accuracy metric used to optimize the predictor.
|
CreatePredictorRequest.Builder |
overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) |
CreatePredictorRequest.Builder |
overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) |
CreatePredictorRequest.Builder |
performAutoML(Boolean performAutoML)
Whether to perform AutoML.
|
CreatePredictorRequest.Builder |
performHPO(Boolean performHPO)
Whether to perform hyperparameter optimization (HPO).
|
CreatePredictorRequest.Builder |
predictorName(String predictorName)
A name for the predictor.
|
CreatePredictorRequest.Builder |
tags(Collection<Tag> tags)
The optional metadata that you apply to the predictor to help you categorize and organize them.
|
CreatePredictorRequest.Builder |
tags(Consumer<Tag.Builder>... tags)
The optional metadata that you apply to the predictor to help you categorize and organize them.
|
CreatePredictorRequest.Builder |
tags(Tag... tags)
The optional metadata that you apply to the predictor to help you categorize and organize them.
|
CreatePredictorRequest.Builder |
trainingParameters(Map<String,String> trainingParameters)
The hyperparameters to override for model training.
|
buildoverrideConfigurationequalsBySdkFields, sdkFieldscopyapplyMutation, buildCreatePredictorRequest.Builder predictorName(String predictorName)
A name for the predictor.
predictorName - A name for the predictor.CreatePredictorRequest.Builder algorithmArn(String algorithmArn)
The Amazon Resource Name (ARN) of the algorithm to use for model training. Required if
PerformAutoML is not set to true.
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
algorithmArn - The Amazon Resource Name (ARN) of the algorithm to use for model training. Required if
PerformAutoML is not set to true.
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
CreatePredictorRequest.Builder forecastHorizon(Integer 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.
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.
CreatePredictorRequest.Builder forecastTypes(Collection<String> 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"].
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"].
CreatePredictorRequest.Builder forecastTypes(String... 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"].
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"].
CreatePredictorRequest.Builder performAutoML(Boolean 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 to true 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.
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 to true 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.
CreatePredictorRequest.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.
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.
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.
AutoMLOverrideStrategy,
AutoMLOverrideStrategyCreatePredictorRequest.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.
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.
AutoMLOverrideStrategy,
AutoMLOverrideStrategyCreatePredictorRequest.Builder performHPO(Boolean 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 to true 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 and PerformAutoML must be false.
The following algorithms support HPO:
DeepAR+
CNN-QR
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 to true 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 and PerformAutoML must be false.
The following algorithms support HPO:
DeepAR+
CNN-QR
CreatePredictorRequest.Builder trainingParameters(Map<String,String> 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.
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.CreatePredictorRequest.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 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 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)CreatePredictorRequest.Builder hpoConfig(HyperParameterTuningJobConfig 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 set PerformHPO to true.
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 set PerformHPO to true.
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 HPOConfig object, you must set PerformHPO to true.
HyperParameterTuningJobConfig.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)CreatePredictorRequest.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 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 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)CreatePredictorRequest.Builder featurizationConfig(FeaturizationConfig featurizationConfig)
The featurization configuration.
featurizationConfig - The featurization configuration.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 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)CreatePredictorRequest.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 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 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)CreatePredictorRequest.Builder tags(Collection<Tag> 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 has aws 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 of aws do not count against your tags per resource limit.
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 has aws 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 of aws do not count against your tags per resource limit.
CreatePredictorRequest.Builder tags(Tag... 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 has aws 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 of aws do not count against your tags per resource limit.
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 has aws 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 of aws do not count against your tags per resource limit.
CreatePredictorRequest.Builder tags(Consumer<Tag.Builder>... 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 has aws 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 of aws do not count against your tags per resource limit.
Tag.Builder avoiding the need to create one manually
via Tag.builder().
When the Consumer completes,
SdkBuilder.build() is called immediately and its
result is passed to #tags(List.
tags - a consumer that will call methods on
Tag.Builder#tags(java.util.Collection) CreatePredictorRequest.Builder optimizationMetric(String optimizationMetric)
The accuracy metric used to optimize the predictor.
optimizationMetric - The accuracy metric used to optimize the predictor.OptimizationMetric,
OptimizationMetricCreatePredictorRequest.Builder optimizationMetric(OptimizationMetric optimizationMetric)
The accuracy metric used to optimize the predictor.
optimizationMetric - The accuracy metric used to optimize the predictor.OptimizationMetric,
OptimizationMetricCreatePredictorRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)
overrideConfiguration in interface AwsRequest.BuilderCreatePredictorRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)
overrideConfiguration in interface AwsRequest.BuilderCopyright © 2023. All rights reserved.