Class: Aws::SageMaker::Types::TimeSeriesForecastingJobConfig
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::TimeSeriesForecastingJobConfig
- Defined in:
- gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb
Overview
The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#candidate_generation_config ⇒ Types::CandidateGenerationConfig
Stores the configuration information for how model candidates are generated using an AutoML job V2.
-
#completion_criteria ⇒ Types::AutoMLJobCompletionCriteria
How long a job is allowed to run, or how many candidates a job is allowed to generate.
-
#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
. -
#forecast_frequency ⇒ String
The frequency of predictions in a forecast.
-
#forecast_horizon ⇒ Integer
The number of time-steps that the model predicts.
-
#forecast_quantiles ⇒ Array<String>
The quantiles used to train the model for forecasts at a specified quantile.
-
#holiday_config ⇒ Array<Types::HolidayConfigAttributes>
The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
-
#time_series_config ⇒ Types::TimeSeriesConfig
The collection of components that defines the time-series.
-
#transformations ⇒ Types::TimeSeriesTransformations
The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
Instance Attribute Details
#candidate_generation_config ⇒ Types::CandidateGenerationConfig
Stores the configuration information for how model candidates are generated using an AutoML job V2.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_config) SENSITIVE = [] include Aws::Structure end |
#completion_criteria ⇒ Types::AutoMLJobCompletionCriteria
How long a job is allowed to run, or how many candidates a job is allowed to generate.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_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
.
TimeSeriesConfig
.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_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
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_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.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_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.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_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.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_config) SENSITIVE = [] include Aws::Structure end |
#time_series_config ⇒ Types::TimeSeriesConfig
The collection of components that defines the time-series.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_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.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 42718 class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config, :candidate_generation_config) SENSITIVE = [] include Aws::Structure end |