java.lang.Object
- software.amazon.awssdk.services.sagemaker.model.AutoMLChannel

All Implemented Interfaces:

Serializable, SdkPojo, ToCopyableBuilder<AutoMLChannel.Builder,AutoMLChannel>
```
@Generated("software.amazon.awssdk:codegen")
public final class AutoMLChannel
extends Object
implements SdkPojo, Serializable, ToCopyableBuilder<AutoMLChannel.Builder,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.

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

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static interface AutoMLChannel.Builder

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`static AutoMLChannel.Builder`	`builder()`
`AutoMLChannelType`	`channelType()`	The channel type (optional) is an `enum` string.
`String`	`channelTypeAsString()`	The channel type (optional) is an `enum` string.
`CompressionType`	`compressionType()`	You can use `Gzip` or `None`.
`String`	`compressionTypeAsString()`	You can use `Gzip` or `None`.
`String`	`contentType()`	The content type of the data from the input source.
`AutoMLDataSource`	`dataSource()`	The data source for an AutoML channel.
`boolean`	`equals(Object obj)`
`boolean`	`equalsBySdkFields(Object obj)`
`<T> Optional<T>`	`getValueForField(String fieldName, Class<T> clazz)`
`int`	`hashCode()`
`String`	`sampleWeightAttributeName()`	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.
`Map<String,SdkField<?>>`	`sdkFieldNameToField()`
`List<SdkField<?>>`	`sdkFields()`
`static Class<? extends AutoMLChannel.Builder>`	`serializableBuilderClass()`
`String`	`targetAttributeName()`	The name of the target variable in supervised learning, usually represented by 'y'.
`AutoMLChannel.Builder`	`toBuilder()`
`String`	`toString()`	Returns a string representation of this object.

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy

- Method Detail
  - dataSource
```
public final AutoMLDataSource dataSource()
```
    The data source for an AutoML channel.
    
    Returns:
    
    The data source for an AutoML channel.
  - compressionType
```
public final CompressionType compressionType()
```
    You can use Gzip or None. The default value is None.
    
    If the service returns an enum value that is not available in the current SDK version, compressionType will return CompressionType.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from compressionTypeAsString().
    
    Returns:
    
    You can use Gzip or None. The default value is None.
    
    See Also:
    
    CompressionType
  - compressionTypeAsString
```
public final String compressionTypeAsString()
```
    You can use Gzip or None. The default value is None.
    
    If the service returns an enum value that is not available in the current SDK version, compressionType will return CompressionType.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from compressionTypeAsString().
    
    Returns:
    
    You can use Gzip or None. The default value is None.
    
    See Also:
    
    CompressionType
  - targetAttributeName
```
public final String targetAttributeName()
```
    The name of the target variable in supervised learning, usually represented by 'y'.
    
    Returns:
    
    The name of the target variable in supervised learning, usually represented by 'y'.
  - contentType
```
public final 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.
    
    Returns:
    
    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.
  - channelType
```
public final 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.
    
    If the service returns an enum value that is not available in the current SDK version, channelType will return AutoMLChannelType.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from channelTypeAsString().
    
    Returns:
    
    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.
    
    See Also:
    
    AutoMLChannelType
  - channelTypeAsString
```
public final String channelTypeAsString()
```
    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.
    
    If the service returns an enum value that is not available in the current SDK version, channelType will return AutoMLChannelType.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from channelTypeAsString().
    
    Returns:
    
    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.
    
    See Also:
    
    AutoMLChannelType
  - sampleWeightAttributeName
```
public final String sampleWeightAttributeName()
```
    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.
    
    Returns:
    
    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.
  - toBuilder
```
public AutoMLChannel.Builder toBuilder()
```
    Specified by:
    
    toBuilder in interface ToCopyableBuilder<AutoMLChannel.Builder,AutoMLChannel>
  - builder
```
public static AutoMLChannel.Builder builder()
```
  - serializableBuilderClass
```
public static Class<? extends AutoMLChannel.Builder> serializableBuilderClass()
```
  - hashCode
```
public final int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - equals
```
public final boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - equalsBySdkFields
```
public final boolean equalsBySdkFields(Object obj)
```
    Specified by:
    
    equalsBySdkFields in interface SdkPojo
  - toString
```
public final String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
  - getValueForField
```
public final <T> Optional<T> getValueForField(String fieldName,
                                              Class<T> clazz)
```
  - sdkFields
```
public final List<SdkField<?>> sdkFields()
```
    Specified by:
    
    sdkFields in interface SdkPojo
  - sdkFieldNameToField
```
public final Map<String,SdkField<?>> sdkFieldNameToField()
```
    Specified by:
    
    sdkFieldNameToField in interface SdkPojo

Class AutoMLChannel

Nested Class Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder

Method Detail

dataSource

compressionType

compressionTypeAsString

targetAttributeName

contentType

channelType

channelTypeAsString

sampleWeightAttributeName

toBuilder

builder

serializableBuilderClass

hashCode

equals

equalsBySdkFields

toString

getValueForField

sdkFields

sdkFieldNameToField