@Generated(value="software.amazon.awssdk:codegen") public final class CreateAutoPredictorRequest extends ForecastRequest implements ToCopyableBuilder<CreateAutoPredictorRequest.Builder,CreateAutoPredictorRequest>
| Modifier and Type | Class and Description |
|---|---|
static interface |
CreateAutoPredictorRequest.Builder |
| Modifier and Type | Method and Description |
|---|---|
static CreateAutoPredictorRequest.Builder |
builder() |
DataConfig |
dataConfig()
The data configuration for your dataset group and any additional datasets.
|
EncryptionConfig |
encryptionConfig()
Returns the value of the EncryptionConfig property for this object.
|
boolean |
equals(Object obj) |
boolean |
equalsBySdkFields(Object obj) |
Boolean |
explainPredictor()
Create an Explainability resource for the predictor.
|
List<String> |
forecastDimensions()
An array of dimension (field) names that specify how to group the generated forecast.
|
String |
forecastFrequency()
The frequency of predictions in a forecast.
|
Integer |
forecastHorizon()
The number of time-steps that the model predicts.
|
List<String> |
forecastTypes()
The forecast types used to train a predictor.
|
<T> Optional<T> |
getValueForField(String fieldName,
Class<T> clazz) |
boolean |
hasForecastDimensions()
For responses, this returns true if the service returned a value for the ForecastDimensions property.
|
boolean |
hasForecastTypes()
For responses, this returns true if the service returned a value for the ForecastTypes property.
|
int |
hashCode() |
boolean |
hasTags()
For responses, this returns true if the service returned a value for the Tags property.
|
MonitorConfig |
monitorConfig()
The configuration details for predictor monitoring.
|
OptimizationMetric |
optimizationMetric()
The accuracy metric used to optimize the predictor.
|
String |
optimizationMetricAsString()
The accuracy metric used to optimize the predictor.
|
String |
predictorName()
A unique name for the predictor
|
String |
referencePredictorArn()
The ARN of the predictor to retrain or upgrade.
|
List<SdkField<?>> |
sdkFields() |
static Class<? extends CreateAutoPredictorRequest.Builder> |
serializableBuilderClass() |
List<Tag> |
tags()
Optional metadata to help you categorize and organize your predictors.
|
TimeAlignmentBoundary |
timeAlignmentBoundary()
The time boundary Forecast uses to align and aggregate any data that doesn't align with your forecast frequency.
|
CreateAutoPredictorRequest.Builder |
toBuilder() |
String |
toString()
Returns a string representation of this object.
|
overrideConfigurationclone, finalize, getClass, notify, notifyAll, wait, wait, waitcopypublic final String predictorName()
A unique name for the predictor
public final Integer forecastHorizon()
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length.
The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the TARGET_TIME_SERIES dataset length. If you are retraining an existing AutoPredictor, then the maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.
If you are upgrading to an AutoPredictor or retraining an existing AutoPredictor, you cannot update the forecast horizon parameter. You can meet this requirement by providing longer time-series in the dataset.
The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the TARGET_TIME_SERIES dataset length. If you are retraining an existing AutoPredictor, then the maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.
If you are upgrading to an AutoPredictor or retraining an existing AutoPredictor, you cannot update the forecast horizon parameter. You can meet this requirement by providing longer time-series in the dataset.
public final boolean hasForecastTypes()
isEmpty() method on the property).
This is useful because the SDK will never return a null collection or map, but you may need to differentiate
between the service returning nothing (or null) and the service returning an empty collection or map. For
requests, this returns true if a value for the property was specified in the request builder, and false if a
value was not specified.public final List<String> forecastTypes()
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.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
This method will never return null. If you would like to know whether the service returned this field (so that
you can differentiate between null and empty), you can use the hasForecastTypes() method.
mean.public final boolean hasForecastDimensions()
isEmpty() method on the property).
This is useful because the SDK will never return a null collection or map, but you may need to differentiate
between the service returning nothing (or null) and the service returning an empty collection or map. For
requests, this returns true if a value for the property was specified in the request builder, and false if a
value was not specified.public final List<String> forecastDimensions()
An array of dimension (field) names that specify how to group the generated forecast.
For example, if you are generating forecasts for item sales across all your stores, and your dataset contains a
store_id field, you would specify store_id as a dimension to group sales forecasts for
each store.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
This method will never return null. If you would like to know whether the service returned this field (so that
you can differentiate between null and empty), you can use the hasForecastDimensions() method.
For example, if you are generating forecasts for item sales across all your stores, and your dataset
contains a store_id field, you would specify store_id as a dimension to group
sales forecasts for each store.
public final String forecastFrequency()
The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".
The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset frequency.
When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to the RELATED_TIME_SERIES dataset frequency.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".
The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset frequency.
When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to the RELATED_TIME_SERIES dataset frequency.
public final DataConfig dataConfig()
The data configuration for your dataset group and any additional datasets.
public final EncryptionConfig encryptionConfig()
public final String referencePredictorArn()
The ARN of the predictor to retrain or upgrade. This parameter is only used when retraining or upgrading a predictor. When creating a new predictor, do not specify a value for this parameter.
When upgrading or retraining a predictor, only specify values for the ReferencePredictorArn and
PredictorName. The value for PredictorName must be a unique predictor name.
When upgrading or retraining a predictor, only specify values for the ReferencePredictorArn
and PredictorName. The value for PredictorName must be a unique predictor name.
public final OptimizationMetric optimizationMetric()
The accuracy metric used to optimize the predictor.
If the service returns an enum value that is not available in the current SDK version,
optimizationMetric will return OptimizationMetric.UNKNOWN_TO_SDK_VERSION. The raw value returned
by the service is available from optimizationMetricAsString().
OptimizationMetricpublic final String optimizationMetricAsString()
The accuracy metric used to optimize the predictor.
If the service returns an enum value that is not available in the current SDK version,
optimizationMetric will return OptimizationMetric.UNKNOWN_TO_SDK_VERSION. The raw value returned
by the service is available from optimizationMetricAsString().
OptimizationMetricpublic final Boolean explainPredictor()
Create an Explainability resource for the predictor.
public final boolean hasTags()
isEmpty() method on the property). This is useful
because the SDK will never return a null collection or map, but you may need to differentiate between the service
returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true
if a value for the property was specified in the request builder, and false if a value was not specified.public final List<Tag> tags()
Optional metadata to help you categorize and organize your predictors. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.
The following restrictions apply to tags:
For each resource, each tag key must be unique and each tag key must have one value.
Maximum number of tags per resource: 50.
Maximum key length: 128 Unicode characters in UTF-8.
Maximum value length: 256 Unicode characters in UTF-8.
Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.
Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values
can have this prefix. If a tag value has aws as its prefix but the key does not, 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. You cannot edit or delete tag keys with this
prefix.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
This method will never return null. If you would like to know whether the service returned this field (so that
you can differentiate between null and empty), you can use the hasTags() method.
The following restrictions apply to tags:
For each resource, each tag key must be unique and each tag key must have one value.
Maximum number of tags per resource: 50.
Maximum key length: 128 Unicode characters in UTF-8.
Maximum value length: 256 Unicode characters in UTF-8.
Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.
Key prefixes cannot include any upper or lowercase combination of aws: or AWS:.
Values can have this prefix. If a tag value has aws as its prefix but the key does not,
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. You cannot edit or
delete tag keys with this prefix.
public final MonitorConfig monitorConfig()
The configuration details for predictor monitoring. Provide a name for the monitor resource to enable predictor monitoring.
Predictor monitoring allows you to see how your predictor's performance changes over time. For more information, see Predictor Monitoring.
Predictor monitoring allows you to see how your predictor's performance changes over time. For more information, see Predictor Monitoring.
public final TimeAlignmentBoundary timeAlignmentBoundary()
The time boundary Forecast uses to align and aggregate any data that doesn't align with your forecast frequency. Provide the unit of time and the time boundary as a key value pair. For more information on specifying a time boundary, see Specifying a Time Boundary. If you don't provide a time boundary, Forecast uses a set of Default Time Boundaries.
public CreateAutoPredictorRequest.Builder toBuilder()
toBuilder in interface ToCopyableBuilder<CreateAutoPredictorRequest.Builder,CreateAutoPredictorRequest>toBuilder in class ForecastRequestpublic static CreateAutoPredictorRequest.Builder builder()
public static Class<? extends CreateAutoPredictorRequest.Builder> serializableBuilderClass()
public final int hashCode()
hashCode in class AwsRequestpublic final boolean equals(Object obj)
equals in class AwsRequestpublic final boolean equalsBySdkFields(Object obj)
equalsBySdkFields in interface SdkPojopublic final String toString()
public final <T> Optional<T> getValueForField(String fieldName, Class<T> clazz)
getValueForField in class SdkRequestCopyright © 2023. All rights reserved.