@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AutoMLChannel extends Object implements Serializable, Cloneable, StructuredPojo
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 .
A validation dataset must contain the same headers as the training dataset.
Constructor and Description |
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AutoMLChannel() |
Modifier and Type | Method and Description |
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AutoMLChannel |
clone() |
boolean |
equals(Object obj) |
String |
getChannelType()
The channel type (optional) is an enum string.
|
String |
getCompressionType()
You can use
Gzip or None . |
String |
getContentType()
The content type of the data from the input source.
|
AutoMLDataSource |
getDataSource()
The data source for an AutoML channel.
|
String |
getTargetAttributeName()
The name of the target variable in supervised learning, usually represented by 'y'.
|
int |
hashCode() |
void |
marshall(ProtocolMarshaller protocolMarshaller)
Marshalls this structured data using the given
ProtocolMarshaller . |
void |
setChannelType(String channelType)
The channel type (optional) is an enum string.
|
void |
setCompressionType(String compressionType)
You can use
Gzip or None . |
void |
setContentType(String contentType)
The content type of the data from the input source.
|
void |
setDataSource(AutoMLDataSource dataSource)
The data source for an AutoML channel.
|
void |
setTargetAttributeName(String targetAttributeName)
The name of the target variable in supervised learning, usually represented by 'y'.
|
String |
toString()
Returns a string representation of this object.
|
AutoMLChannel |
withChannelType(AutoMLChannelType channelType)
The channel type (optional) is an enum string.
|
AutoMLChannel |
withChannelType(String channelType)
The channel type (optional) is an enum string.
|
AutoMLChannel |
withCompressionType(CompressionType compressionType)
You can use
Gzip or None . |
AutoMLChannel |
withCompressionType(String compressionType)
You can use
Gzip or None . |
AutoMLChannel |
withContentType(String contentType)
The content type of the data from the input source.
|
AutoMLChannel |
withDataSource(AutoMLDataSource dataSource)
The data source for an AutoML channel.
|
AutoMLChannel |
withTargetAttributeName(String targetAttributeName)
The name of the target variable in supervised learning, usually represented by 'y'.
|
public void setDataSource(AutoMLDataSource dataSource)
The data source for an AutoML channel.
dataSource
- The data source for an AutoML channel.public AutoMLDataSource getDataSource()
The data source for an AutoML channel.
public AutoMLChannel withDataSource(AutoMLDataSource dataSource)
The data source for an AutoML channel.
dataSource
- The data source for an AutoML channel.public void setCompressionType(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
public String getCompressionType()
You can use Gzip
or None
. The default value is None
.
Gzip
or None
. The default value is None
.CompressionType
public AutoMLChannel withCompressionType(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
public AutoMLChannel withCompressionType(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
public void setTargetAttributeName(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'.public String getTargetAttributeName()
The name of the target variable in supervised learning, usually represented by 'y'.
public AutoMLChannel withTargetAttributeName(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'.public void setContentType(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
.public String getContentType()
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
.
text/csv;header=present
or
x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.public AutoMLChannel withContentType(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
.public void setChannelType(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
.
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
.AutoMLChannelType
public String getChannelType()
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
.
training
. Channels for
training and validation must share the same ContentType
and TargetAttributeName
.AutoMLChannelType
public AutoMLChannel withChannelType(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
.
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
.AutoMLChannelType
public AutoMLChannel withChannelType(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
.
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
.AutoMLChannelType
public String toString()
toString
in class Object
Object.toString()
public AutoMLChannel clone()
public void marshall(ProtocolMarshaller protocolMarshaller)
StructuredPojo
ProtocolMarshaller
.marshall
in interface StructuredPojo
protocolMarshaller
- Implementation of ProtocolMarshaller
used to marshall this object's data.