Class: Aws::SageMaker::Types::AutoMLChannel

Inherits:

Struct

• Object
• Struct
• Aws::SageMaker::Types::AutoMLChannel

Defined in:

gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb

Overview

A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.

A validation dataset must contain the same headers as the training dataset.

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #channel_type ⇒ String

  The channel type (optional) is an enum string.

• #compression_type ⇒ String

  You can use Gzip or None.

• #content_type ⇒ String

  The content type of the data from the input source.

• #data_source ⇒ Types::AutoMLDataSource

  The data source for an AutoML channel.

• #sample_weight_attribute_name ⇒ String

  If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model.

• #target_attribute_name ⇒ String

  The name of the target variable in supervised learning, usually represented by 'y'.

Instance Attribute Details

#channel_type ⇒ String

The channel type (optional) is an enum string. The default value is training. Channels for training and validation must share the same ContentType and TargetAttributeName. For information on specifying training and validation channel types, see How to specify training and validation datasets.

Returns:

• (String)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2013

class AutoMLChannel < Struct.new(
  :data_source,
  :compression_type,
  :target_attribute_name,
  :content_type,
  :channel_type,
  :sample_weight_attribute_name)
  SENSITIVE = []
  include Aws::Structure
end

#compression_type ⇒ String

You can use Gzip or None. The default value is None.

Returns:

• (String)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2013

class AutoMLChannel < Struct.new(
  :data_source,
  :compression_type,
  :target_attribute_name,
  :content_type,
  :channel_type,
  :sample_weight_attribute_name)
  SENSITIVE = []
  include Aws::Structure
end

#content_type ⇒ String

The content type of the data from the input source. You can use text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.

Returns:

• (String)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2013

class AutoMLChannel < Struct.new(
  :data_source,
  :compression_type,
  :target_attribute_name,
  :content_type,
  :channel_type,
  :sample_weight_attribute_name)
  SENSITIVE = []
  include Aws::Structure
end

#data_source ⇒ Types::AutoMLDataSource

The data source for an AutoML channel.

Returns:

• (Types::AutoMLDataSource)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2013

class AutoMLChannel < Struct.new(
  :data_source,
  :compression_type,
  :target_attribute_name,
  :content_type,
  :channel_type,
  :sample_weight_attribute_name)
  SENSITIVE = []
  include Aws::Structure
end

#sample_weight_attribute_name ⇒ String

If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.

Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.

Support for sample weights is available in Ensembling mode only.

Returns:

• (String)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2013

class AutoMLChannel < Struct.new(
  :data_source,
  :compression_type,
  :target_attribute_name,
  :content_type,
  :channel_type,
  :sample_weight_attribute_name)
  SENSITIVE = []
  include Aws::Structure
end

#target_attribute_name ⇒ String

The name of the target variable in supervised learning, usually represented by 'y'.

Returns:

• (String)

# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2013

class AutoMLChannel < Struct.new(
  :data_source,
  :compression_type,
  :target_attribute_name,
  :content_type,
  :channel_type,
  :sample_weight_attribute_name)
  SENSITIVE = []
  include Aws::Structure
end