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

Inherits:

Struct

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

Includes:

Aws::Structure

Defined in:

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].

<note markdown=“1”> A validation dataset must contain the same headers as the training dataset.

</note>

[1]: docs.aws.amazon.com/sagemaker/latest/APIReference/API_Channel.html

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].

[1]: docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-data-sources-training-or-validation

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 2089

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 'lib/aws-sdk-sagemaker/types.rb', line 2089

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 'lib/aws-sdk-sagemaker/types.rb', line 2089

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 'lib/aws-sdk-sagemaker/types.rb', line 2089

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.

[1]: docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.html [2]: docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 2089

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 'lib/aws-sdk-sagemaker/types.rb', line 2089

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