public static interface AutoMLChannel.Builder extends SdkPojo, CopyableBuilder<AutoMLChannel.Builder,AutoMLChannel>
| Modifier and Type | Method and Description |
|---|---|
AutoMLChannel.Builder |
channelType(AutoMLChannelType channelType)
The channel type (optional) is an
enum string. |
AutoMLChannel.Builder |
channelType(String channelType)
The channel type (optional) is an
enum string. |
AutoMLChannel.Builder |
compressionType(CompressionType compressionType)
You can use
Gzip or None. |
AutoMLChannel.Builder |
compressionType(String compressionType)
You can use
Gzip or None. |
AutoMLChannel.Builder |
contentType(String contentType)
The content type of the data from the input source.
|
AutoMLChannel.Builder |
dataSource(AutoMLDataSource dataSource)
The data source for an AutoML channel.
|
default AutoMLChannel.Builder |
dataSource(Consumer<AutoMLDataSource.Builder> dataSource)
The data source for an AutoML channel.
|
AutoMLChannel.Builder |
targetAttributeName(String targetAttributeName)
The name of the target variable in supervised learning, usually represented by 'y'.
|
equalsBySdkFields, sdkFieldscopyapplyMutation, buildAutoMLChannel.Builder dataSource(AutoMLDataSource dataSource)
The data source for an AutoML channel.
dataSource - The data source for an AutoML channel.default AutoMLChannel.Builder dataSource(Consumer<AutoMLDataSource.Builder> dataSource)
The data source for an AutoML channel.
This is a convenience method that creates an instance of theAutoMLDataSource.Builder avoiding the
need to create one manually via AutoMLDataSource.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to dataSource(AutoMLDataSource).dataSource - a consumer that will call methods on AutoMLDataSource.BuilderdataSource(AutoMLDataSource)AutoMLChannel.Builder compressionType(String compressionType)
You can use Gzip or None. The default value is None.
compressionType - You can use Gzip or None. The default value is None.CompressionType,
CompressionTypeAutoMLChannel.Builder compressionType(CompressionType compressionType)
You can use Gzip or None. The default value is None.
compressionType - You can use Gzip or None. The default value is None.CompressionType,
CompressionTypeAutoMLChannel.Builder targetAttributeName(String targetAttributeName)
The name of the target variable in supervised learning, usually represented by 'y'.
targetAttributeName - The name of the target variable in supervised learning, usually represented by 'y'.AutoMLChannel.Builder contentType(String 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.
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.AutoMLChannel.Builder channelType(String 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 .
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 .AutoMLChannelType,
AutoMLChannelTypeAutoMLChannel.Builder channelType(AutoMLChannelType 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 .
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 .AutoMLChannelType,
AutoMLChannelTypeCopyright © 2022. All rights reserved.