Interface FeaturizationConfig.Builder
- All Superinterfaces:
Buildable
,CopyableBuilder<FeaturizationConfig.Builder,
,FeaturizationConfig> SdkBuilder<FeaturizationConfig.Builder,
,FeaturizationConfig> SdkPojo
- Enclosing class:
FeaturizationConfig
-
Method Summary
Modifier and TypeMethodDescriptionfeaturizations
(Collection<Featurization> featurizations) An array of featurization (transformation) information for the fields of a dataset.featurizations
(Consumer<Featurization.Builder>... featurizations) An array of featurization (transformation) information for the fields of a dataset.featurizations
(Featurization... featurizations) An array of featurization (transformation) information for the fields of a dataset.forecastDimensions
(String... forecastDimensions) An array of dimension (field) names that specify how to group the generated forecast.forecastDimensions
(Collection<String> forecastDimensions) An array of dimension (field) names that specify how to group the generated forecast.forecastFrequency
(String forecastFrequency) The frequency of predictions in a forecast.Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copy
Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, build
Methods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFields
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Method Details
-
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
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Hour - 1-23
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Day - 1-6
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Week - 1-4
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Month - 1-11
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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 TARGET_TIME_SERIES dataset frequency.
- Parameters:
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 TARGET_TIME_SERIES dataset frequency.
-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
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forecastDimensions
An array of dimension (field) names that specify how to group the generated forecast.
For example, suppose that you are generating a forecast for item sales across all of your stores, and your dataset contains a
store_id
field. If you want the sales forecast for each item by store, you would specifystore_id
as the dimension.All forecast dimensions specified in the
TARGET_TIME_SERIES
dataset don't need to be specified in theCreatePredictor
request. All forecast dimensions specified in theRELATED_TIME_SERIES
dataset must be specified in theCreatePredictor
request.- Parameters:
forecastDimensions
- An array of dimension (field) names that specify how to group the generated forecast.For example, suppose that you are generating a forecast for item sales across all of your stores, and your dataset contains a
store_id
field. If you want the sales forecast for each item by store, you would specifystore_id
as the dimension.All forecast dimensions specified in the
TARGET_TIME_SERIES
dataset don't need to be specified in theCreatePredictor
request. All forecast dimensions specified in theRELATED_TIME_SERIES
dataset must be specified in theCreatePredictor
request.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
forecastDimensions
An array of dimension (field) names that specify how to group the generated forecast.
For example, suppose that you are generating a forecast for item sales across all of your stores, and your dataset contains a
store_id
field. If you want the sales forecast for each item by store, you would specifystore_id
as the dimension.All forecast dimensions specified in the
TARGET_TIME_SERIES
dataset don't need to be specified in theCreatePredictor
request. All forecast dimensions specified in theRELATED_TIME_SERIES
dataset must be specified in theCreatePredictor
request.- Parameters:
forecastDimensions
- An array of dimension (field) names that specify how to group the generated forecast.For example, suppose that you are generating a forecast for item sales across all of your stores, and your dataset contains a
store_id
field. If you want the sales forecast for each item by store, you would specifystore_id
as the dimension.All forecast dimensions specified in the
TARGET_TIME_SERIES
dataset don't need to be specified in theCreatePredictor
request. All forecast dimensions specified in theRELATED_TIME_SERIES
dataset must be specified in theCreatePredictor
request.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
featurizations
An array of featurization (transformation) information for the fields of a dataset.
- Parameters:
featurizations
- An array of featurization (transformation) information for the fields of a dataset.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
featurizations
An array of featurization (transformation) information for the fields of a dataset.
- Parameters:
featurizations
- An array of featurization (transformation) information for the fields of a dataset.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
featurizations
An array of featurization (transformation) information for the fields of a dataset.
This is a convenience method that creates an instance of theFeaturization.Builder
avoiding the need to create one manually viaFeaturization.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tofeaturizations(List<Featurization>)
.- Parameters:
featurizations
- a consumer that will call methods onFeaturization.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-