AWS SDK for C++  1.9.66
AWS SDK for C++
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Aws::ForecastService::Model::FeaturizationConfig Class Reference

#include <FeaturizationConfig.h>

Public Member Functions

 FeaturizationConfig ()
 
 FeaturizationConfig (Aws::Utils::Json::JsonView jsonValue)
 
FeaturizationConfigoperator= (Aws::Utils::Json::JsonView jsonValue)
 
Aws::Utils::Json::JsonValue Jsonize () const
 
const Aws::StringGetForecastFrequency () const
 
bool ForecastFrequencyHasBeenSet () const
 
void SetForecastFrequency (const Aws::String &value)
 
void SetForecastFrequency (Aws::String &&value)
 
void SetForecastFrequency (const char *value)
 
FeaturizationConfigWithForecastFrequency (const Aws::String &value)
 
FeaturizationConfigWithForecastFrequency (Aws::String &&value)
 
FeaturizationConfigWithForecastFrequency (const char *value)
 
const Aws::Vector< Aws::String > & GetForecastDimensions () const
 
bool ForecastDimensionsHasBeenSet () const
 
void SetForecastDimensions (const Aws::Vector< Aws::String > &value)
 
void SetForecastDimensions (Aws::Vector< Aws::String > &&value)
 
FeaturizationConfigWithForecastDimensions (const Aws::Vector< Aws::String > &value)
 
FeaturizationConfigWithForecastDimensions (Aws::Vector< Aws::String > &&value)
 
FeaturizationConfigAddForecastDimensions (const Aws::String &value)
 
FeaturizationConfigAddForecastDimensions (Aws::String &&value)
 
FeaturizationConfigAddForecastDimensions (const char *value)
 
const Aws::Vector< Featurization > & GetFeaturizations () const
 
bool FeaturizationsHasBeenSet () const
 
void SetFeaturizations (const Aws::Vector< Featurization > &value)
 
void SetFeaturizations (Aws::Vector< Featurization > &&value)
 
FeaturizationConfigWithFeaturizations (const Aws::Vector< Featurization > &value)
 
FeaturizationConfigWithFeaturizations (Aws::Vector< Featurization > &&value)
 
FeaturizationConfigAddFeaturizations (const Featurization &value)
 
FeaturizationConfigAddFeaturizations (Featurization &&value)
 

Detailed Description

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.

See Also:

AWS API Reference

Definition at line 45 of file FeaturizationConfig.h.

Constructor & Destructor Documentation

◆ FeaturizationConfig() [1/2]

Aws::ForecastService::Model::FeaturizationConfig::FeaturizationConfig ( )

◆ FeaturizationConfig() [2/2]

Aws::ForecastService::Model::FeaturizationConfig::FeaturizationConfig ( Aws::Utils::Json::JsonView  jsonValue)

Member Function Documentation

◆ AddFeaturizations() [1/2]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::AddFeaturizations ( const Featurization value)
inline

An array of featurization (transformation) information for the fields of a dataset.

Definition at line 301 of file FeaturizationConfig.h.

◆ AddFeaturizations() [2/2]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::AddFeaturizations ( Featurization &&  value)
inline

An array of featurization (transformation) information for the fields of a dataset.

Definition at line 307 of file FeaturizationConfig.h.

◆ AddForecastDimensions() [1/3]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::AddForecastDimensions ( Aws::String &&  value)
inline

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.

Definition at line 245 of file FeaturizationConfig.h.

◆ AddForecastDimensions() [2/3]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::AddForecastDimensions ( const Aws::String value)
inline

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.

Definition at line 232 of file FeaturizationConfig.h.

◆ AddForecastDimensions() [3/3]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::AddForecastDimensions ( const char *  value)
inline

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.

Definition at line 258 of file FeaturizationConfig.h.

◆ FeaturizationsHasBeenSet()

bool Aws::ForecastService::Model::FeaturizationConfig::FeaturizationsHasBeenSet ( ) const
inline

An array of featurization (transformation) information for the fields of a dataset.

Definition at line 271 of file FeaturizationConfig.h.

◆ ForecastDimensionsHasBeenSet()

bool Aws::ForecastService::Model::FeaturizationConfig::ForecastDimensionsHasBeenSet ( ) const
inline

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.

Definition at line 167 of file FeaturizationConfig.h.

◆ ForecastFrequencyHasBeenSet()

bool Aws::ForecastService::Model::FeaturizationConfig::ForecastFrequencyHasBeenSet ( ) const
inline

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.

Definition at line 74 of file FeaturizationConfig.h.

◆ GetFeaturizations()

const Aws::Vector<Featurization>& Aws::ForecastService::Model::FeaturizationConfig::GetFeaturizations ( ) const
inline

An array of featurization (transformation) information for the fields of a dataset.

Definition at line 265 of file FeaturizationConfig.h.

◆ GetForecastDimensions()

const Aws::Vector<Aws::String>& Aws::ForecastService::Model::FeaturizationConfig::GetForecastDimensions ( ) const
inline

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.

Definition at line 154 of file FeaturizationConfig.h.

◆ GetForecastFrequency()

const Aws::String& Aws::ForecastService::Model::FeaturizationConfig::GetForecastFrequency ( ) const
inline

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.

Definition at line 63 of file FeaturizationConfig.h.

◆ Jsonize()

Aws::Utils::Json::JsonValue Aws::ForecastService::Model::FeaturizationConfig::Jsonize ( ) const

◆ operator=()

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::operator= ( Aws::Utils::Json::JsonView  jsonValue)

◆ SetFeaturizations() [1/2]

void Aws::ForecastService::Model::FeaturizationConfig::SetFeaturizations ( Aws::Vector< Featurization > &&  value)
inline

An array of featurization (transformation) information for the fields of a dataset.

Definition at line 283 of file FeaturizationConfig.h.

◆ SetFeaturizations() [2/2]

void Aws::ForecastService::Model::FeaturizationConfig::SetFeaturizations ( const Aws::Vector< Featurization > &  value)
inline

An array of featurization (transformation) information for the fields of a dataset.

Definition at line 277 of file FeaturizationConfig.h.

◆ SetForecastDimensions() [1/2]

void Aws::ForecastService::Model::FeaturizationConfig::SetForecastDimensions ( Aws::Vector< Aws::String > &&  value)
inline

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.

Definition at line 193 of file FeaturizationConfig.h.

◆ SetForecastDimensions() [2/2]

void Aws::ForecastService::Model::FeaturizationConfig::SetForecastDimensions ( const Aws::Vector< Aws::String > &  value)
inline

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.

Definition at line 180 of file FeaturizationConfig.h.

◆ SetForecastFrequency() [1/3]

void Aws::ForecastService::Model::FeaturizationConfig::SetForecastFrequency ( Aws::String &&  value)
inline

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.

Definition at line 96 of file FeaturizationConfig.h.

◆ SetForecastFrequency() [2/3]

void Aws::ForecastService::Model::FeaturizationConfig::SetForecastFrequency ( const Aws::String value)
inline

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.

Definition at line 85 of file FeaturizationConfig.h.

◆ SetForecastFrequency() [3/3]

void Aws::ForecastService::Model::FeaturizationConfig::SetForecastFrequency ( const char *  value)
inline

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.

Definition at line 107 of file FeaturizationConfig.h.

◆ WithFeaturizations() [1/2]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::WithFeaturizations ( Aws::Vector< Featurization > &&  value)
inline

An array of featurization (transformation) information for the fields of a dataset.

Definition at line 295 of file FeaturizationConfig.h.

◆ WithFeaturizations() [2/2]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::WithFeaturizations ( const Aws::Vector< Featurization > &  value)
inline

An array of featurization (transformation) information for the fields of a dataset.

Definition at line 289 of file FeaturizationConfig.h.

◆ WithForecastDimensions() [1/2]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::WithForecastDimensions ( Aws::Vector< Aws::String > &&  value)
inline

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.

Definition at line 219 of file FeaturizationConfig.h.

◆ WithForecastDimensions() [2/2]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::WithForecastDimensions ( const Aws::Vector< Aws::String > &  value)
inline

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.

Definition at line 206 of file FeaturizationConfig.h.

◆ WithForecastFrequency() [1/3]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::WithForecastFrequency ( Aws::String &&  value)
inline

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.

Definition at line 129 of file FeaturizationConfig.h.

◆ WithForecastFrequency() [2/3]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::WithForecastFrequency ( const Aws::String value)
inline

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.

Definition at line 118 of file FeaturizationConfig.h.

◆ WithForecastFrequency() [3/3]

FeaturizationConfig& Aws::ForecastService::Model::FeaturizationConfig::WithForecastFrequency ( const char *  value)
inline

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.

Definition at line 140 of file FeaturizationConfig.h.


The documentation for this class was generated from the following file: