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:

  • Method Details

    • 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:

    • 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:

    • 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:

    • 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:

    • 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()
      Description copied from interface: ToCopyableBuilder
      Take this object and create a builder that contains all of the current property values of this object.
      Specified by:
      toBuilder in interface ToCopyableBuilder<AutoMLChannel.Builder,AutoMLChannel>
      Returns:
      a builder for type T

    • 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)
      Description copied from interface: SdkPojo
      Indicates whether some other object is "equal to" this one by SDK fields. An SDK field is a modeled, non-inherited field in an SdkPojo class, and is generated based on a service model.

      If an SdkPojo class does not have any inherited fields, equalsBySdkFields and equals are essentially the same.

      Specified by:
      equalsBySdkFields in interface SdkPojo
      Parameters:
      obj - the object to be compared with
      Returns:
      true if the other object equals to this object by sdk fields, false otherwise.

    • 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
      Returns:
      List of SdkField in this POJO. May be empty list but should never be null.