software.amazon.awssdk.services.sagemaker.model

Class AutoMLJobObjective

java.lang.Object

software.amazon.awssdk.services.sagemaker.model.AutoMLJobObjective

All Implemented Interfaces:

Serializable, SdkPojo, ToCopyableBuilder<AutoMLJobObjective.Builder,AutoMLJobObjective>

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

Specifies a metric to minimize or maximize as the objective of a job.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static interface	AutoMLJobObjective.Builder

Method Summary

Modifier and Type	Method and Description
static AutoMLJobObjective.Builder	builder()
boolean	equals(Object obj)
boolean	equalsBySdkFields(Object obj)
<T> Optional<T>	getValueForField(String fieldName, Class<T> clazz)
int	hashCode()
AutoMLMetricEnum	metricName() The name of the objective metric used to measure the predictive quality of a machine learning system.
String	metricNameAsString() The name of the objective metric used to measure the predictive quality of a machine learning system.
List<SdkField<?>>	sdkFields()
static Class<? extends AutoMLJobObjective.Builder>	serializableBuilderClass()
AutoMLJobObjective.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

metricName

public final AutoMLMetricEnum metricName()

The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.

For the list of all available metrics supported by Autopilot, see Autopilot metrics.

If you do not specify a metric explicitly, the default behavior is to automatically use:

• For tabular problem types:

  • Regression: MSE.

  • Binary classification: F1.

  • Multiclass classification: Accuracy.

• For image or text classification problem types: Accuracy

If the service returns an enum value that is not available in the current SDK version, metricName will return AutoMLMetricEnum.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from metricNameAsString().

Returns:

The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.

For the list of all available metrics supported by Autopilot, see Autopilot metrics.

If you do not specify a metric explicitly, the default behavior is to automatically use:

• For tabular problem types:

  • Regression: MSE.

  • Binary classification: F1.

  • Multiclass classification: Accuracy.

• For image or text classification problem types: Accuracy

See Also:

AutoMLMetricEnum

metricNameAsString

public final String metricNameAsString()

The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.

For the list of all available metrics supported by Autopilot, see Autopilot metrics.

If you do not specify a metric explicitly, the default behavior is to automatically use:

• For tabular problem types:

  • Regression: MSE.

  • Binary classification: F1.

  • Multiclass classification: Accuracy.

• For image or text classification problem types: Accuracy

If the service returns an enum value that is not available in the current SDK version, metricName will return AutoMLMetricEnum.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from metricNameAsString().

Returns:

The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.

For the list of all available metrics supported by Autopilot, see Autopilot metrics.

If you do not specify a metric explicitly, the default behavior is to automatically use:

• For tabular problem types:

  • Regression: MSE.

  • Binary classification: F1.

  • Multiclass classification: Accuracy.

• For image or text classification problem types: Accuracy

See Also:

AutoMLMetricEnum

toBuilder

public AutoMLJobObjective.Builder toBuilder()

Specified by:

toBuilder in interface ToCopyableBuilder<AutoMLJobObjective.Builder,AutoMLJobObjective>

builder

public static AutoMLJobObjective.Builder builder()

serializableBuilderClass

public static Class<? extends AutoMLJobObjective.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