Package software.amazon.awssdk.services.sagemaker.model

Class AutoMLChannel

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

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.
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