Class: Aws::SageMaker::Types::TimeSeriesForecastingJobConfig

Inherits:
Struct
  • Object
show all
Includes:
Aws::Structure
Defined in:
lib/aws-sdk-sagemaker/types.rb

Overview

The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.

See Also:

Constant Summary collapse

SENSITIVE = 
[]

Instance Attribute Summary collapse

Instance Attribute Details

#completion_criteria ⇒ Types::AutoMLJobCompletionCriteria

How long a job is allowed to run, or how many candidates a job is allowed to generate.

Returns:



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# File 'lib/aws-sdk-sagemaker/types.rb', line 38106

class TimeSeriesForecastingJobConfig < Struct.new(
  :feature_specification_s3_uri,
  :completion_criteria,
  :forecast_frequency,
  :forecast_horizon,
  :forecast_quantiles,
  :transformations,
  :time_series_config,
  :holiday_config)
  SENSITIVE = []
  include Aws::Structure
end

#feature_specification_s3_uri ⇒ String

A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in ‘TimeSeriesConfig`. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in `TimeSeriesConfig`. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in `TimeSeriesConfig`.

You can input ‘FeatureAttributeNames` (optional) in JSON format as shown below:

‘{ “FeatureAttributeNames”:[“col1”, “col2”, …] }`.

You can also specify the data type of the feature (optional) in the format shown below:

‘{ “FeatureDataTypes”:{“col1”:“numeric”, “col2”:“categorical” … } }`

Autopilot supports the following data types: ‘numeric`, `categorical`, `text`, and `datetime`.

<note markdown=“1”> These column keys must not include any column set in ‘TimeSeriesConfig`.

</note>

Returns:

  • (String) 


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# File 'lib/aws-sdk-sagemaker/types.rb', line 38106

class TimeSeriesForecastingJobConfig < Struct.new(
  :feature_specification_s3_uri,
  :completion_criteria,
  :forecast_frequency,
  :forecast_horizon,
  :forecast_quantiles,
  :transformations,
  :time_series_config,
  :holiday_config)
  SENSITIVE = []
  include Aws::Structure
end

#forecast_frequency ⇒ String

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. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of `1H` instead of `60min`.

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

Returns:

  • (String) 


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# File 'lib/aws-sdk-sagemaker/types.rb', line 38106

class TimeSeriesForecastingJobConfig < Struct.new(
  :feature_specification_s3_uri,
  :completion_criteria,
  :forecast_frequency,
  :forecast_horizon,
  :forecast_quantiles,
  :transformations,
  :time_series_config,
  :holiday_config)
  SENSITIVE = []
  include Aws::Structure
end

#forecast_horizon ⇒ Integer

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 time-steps in the dataset.

Returns:

  • (Integer) 


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# File 'lib/aws-sdk-sagemaker/types.rb', line 38106

class TimeSeriesForecastingJobConfig < Struct.new(
  :feature_specification_s3_uri,
  :completion_criteria,
  :forecast_frequency,
  :forecast_horizon,
  :forecast_quantiles,
  :transformations,
  :time_series_config,
  :holiday_config)
  SENSITIVE = []
  include Aws::Structure
end

#forecast_quantiles ⇒ Array<String>

The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from ‘0.01` (p1) to `0.99` (p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When `ForecastQuantiles` is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.

Returns:

  • (Array<String>) 


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# File 'lib/aws-sdk-sagemaker/types.rb', line 38106

class TimeSeriesForecastingJobConfig < Struct.new(
  :feature_specification_s3_uri,
  :completion_criteria,
  :forecast_frequency,
  :forecast_horizon,
  :forecast_quantiles,
  :transformations,
  :time_series_config,
  :holiday_config)
  SENSITIVE = []
  include Aws::Structure
end

#holiday_config ⇒ Array<Types::HolidayConfigAttributes>

The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.

Returns:



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# File 'lib/aws-sdk-sagemaker/types.rb', line 38106

class TimeSeriesForecastingJobConfig < Struct.new(
  :feature_specification_s3_uri,
  :completion_criteria,
  :forecast_frequency,
  :forecast_horizon,
  :forecast_quantiles,
  :transformations,
  :time_series_config,
  :holiday_config)
  SENSITIVE = []
  include Aws::Structure
end

#time_series_config ⇒ Types::TimeSeriesConfig

The collection of components that defines the time-series.

Returns:



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# File 'lib/aws-sdk-sagemaker/types.rb', line 38106

class TimeSeriesForecastingJobConfig < Struct.new(
  :feature_specification_s3_uri,
  :completion_criteria,
  :forecast_frequency,
  :forecast_horizon,
  :forecast_quantiles,
  :transformations,
  :time_series_config,
  :holiday_config)
  SENSITIVE = []
  include Aws::Structure
end

#transformations ⇒ Types::TimeSeriesTransformations

The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.

Returns:



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# File 'lib/aws-sdk-sagemaker/types.rb', line 38106

class TimeSeriesForecastingJobConfig < Struct.new(
  :feature_specification_s3_uri,
  :completion_criteria,
  :forecast_frequency,
  :forecast_horizon,
  :forecast_quantiles,
  :transformations,
  :time_series_config,
  :holiday_config)
  SENSITIVE = []
  include Aws::Structure
end