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

Inherits:
Struct
  • Object
show all
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

Constant Summary collapse

SENSITIVE =
[]

Instance Attribute Summary collapse

Instance Attribute Details

#channel_typeString

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)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 2086

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_typeString

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

Returns:

  • (String)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 2086

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_typeString

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)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 2086

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_sourceTypes::AutoMLDataSource

The data source for an AutoML channel.



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# File 'lib/aws-sdk-sagemaker/types.rb', line 2086

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_nameString

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)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 2086

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_nameString

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

Returns:

  • (String)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 2086

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