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AWS::SageMaker::AutoMLJob AutoMLChannel - Amazon CloudFormation
SyntaxProperties
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AWS::SageMaker::AutoMLJob AutoMLChannel

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

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

Syntax

To declare this entity in your Amazon CloudFormation template, use the following syntax:

JSON

{
  "ChannelType" : String,
  "CompressionType" : String,
  "ContentType" : String,
  "DataSource" : AutoMLDataSource,
  "TargetAttributeName" : String
}

Properties

ChannelType

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.

Required: No

Type: String

Allowed values: training | validation

Update requires: Replacement

CompressionType

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

Required: No

Type: String

Allowed values: None | Gzip

Update requires: Replacement

ContentType

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.

Required: No

Type: String

Maximum: 256

Update requires: Replacement

DataSource

The data source for an AutoML channel.

Required: No

Type: AutoMLDataSource

Update requires: Replacement

TargetAttributeName

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

Required: Yes

Type: String

Minimum: 1

Update requires: Replacement