@Generated(value="software.amazon.awssdk:codegen") public final class FeaturizationConfig extends Object implements SdkPojo, Serializable, ToCopyableBuilder<FeaturizationConfig.Builder,FeaturizationConfig>
In a CreatePredictor operation, the specified algorithm trains a model using the specified dataset group. You can optionally tell the operation to modify data fields prior to training a model. These modifications are referred to as featurization.
You define featurization using the FeaturizationConfig object. You specify an array of transformations,
one for each field that you want to featurize. You then include the FeaturizationConfig object in your
CreatePredictor request. Amazon Forecast applies the featurization to the
TARGET_TIME_SERIES and RELATED_TIME_SERIES datasets before model training.
You can create multiple featurization configurations. For example, you might call the CreatePredictor
operation twice by specifying different featurization configurations.
| Modifier and Type | Class and Description |
|---|---|
static interface |
FeaturizationConfig.Builder |
| Modifier and Type | Method and Description |
|---|---|
static FeaturizationConfig.Builder |
builder() |
boolean |
equals(Object obj) |
boolean |
equalsBySdkFields(Object obj) |
List<Featurization> |
featurizations()
An array of featurization (transformation) information for the fields of a dataset.
|
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.
|
<T> Optional<T> |
getValueForField(String fieldName,
Class<T> clazz) |
boolean |
hasFeaturizations()
Returns true if the Featurizations property was specified by the sender (it may be empty), or false if the sender
did not specify the value (it will be empty).
|
boolean |
hasForecastDimensions()
Returns true if the ForecastDimensions property was specified by the sender (it may be empty), or false if the
sender did not specify the value (it will be empty).
|
int |
hashCode() |
List<SdkField<?>> |
sdkFields() |
static Class<? extends FeaturizationConfig.Builder> |
serializableBuilderClass() |
FeaturizationConfig.Builder |
toBuilder() |
String |
toString()
Returns a string representation of this object.
|
clone, finalize, getClass, notify, notifyAll, wait, wait, waitcopypublic String forecastFrequency()
The frequency of predictions in a forecast.
Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, "Y" indicates every year and "5min" indicates every five minutes.
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 Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, "Y" indicates every year and "5min" indicates every five minutes.
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 boolean hasForecastDimensions()
public List<String> 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
specify store_id as the dimension.
All forecast dimensions specified in the TARGET_TIME_SERIES dataset don't need to be specified in
the CreatePredictor request. All forecast dimensions specified in the
RELATED_TIME_SERIES dataset must be specified in the CreatePredictor request.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
You can use hasForecastDimensions() to see if a value was sent in this field.
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 specify store_id as the dimension.
All forecast dimensions specified in the TARGET_TIME_SERIES dataset don't need to be
specified in the CreatePredictor request. All forecast dimensions specified in the
RELATED_TIME_SERIES dataset must be specified in the CreatePredictor request.
public boolean hasFeaturizations()
public List<Featurization> featurizations()
An array of featurization (transformation) information for the fields of a dataset.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
You can use hasFeaturizations() to see if a value was sent in this field.
public FeaturizationConfig.Builder toBuilder()
toBuilder in interface ToCopyableBuilder<FeaturizationConfig.Builder,FeaturizationConfig>public static FeaturizationConfig.Builder builder()
public static Class<? extends FeaturizationConfig.Builder> serializableBuilderClass()
public boolean equalsBySdkFields(Object obj)
equalsBySdkFields in interface SdkPojopublic String toString()
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