software.amazon.awssdk.services.frauddetector.model

Class TrainingMetrics

java.lang.Object

software.amazon.awssdk.services.frauddetector.model.TrainingMetrics

All Implemented Interfaces:

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

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

The training metric details.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static interface	TrainingMetrics.Builder

Method Summary

Modifier and Type	Method and Description
Float	auc() The area under the curve.
static TrainingMetrics.Builder	builder()
boolean	equals(Object obj)
boolean	equalsBySdkFields(Object obj)
<T> Optional<T>	getValueForField(String fieldName, Class<T> clazz)
int	hashCode()
boolean	hasMetricDataPoints() Returns true if the MetricDataPoints property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty).
List<MetricDataPoint>	metricDataPoints() The data points details.
List<SdkField<?>>	sdkFields()
static Class<? extends TrainingMetrics.Builder>	serializableBuilderClass()
TrainingMetrics.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

auc

public final Float auc()

The area under the curve. This summarizes true positive rate (TPR) and false positive rate (FPR) across all possible model score thresholds. A model with no predictive power has an AUC of 0.5, whereas a perfect model has a score of 1.0.

Returns:

The area under the curve. This summarizes true positive rate (TPR) and false positive rate (FPR) across all possible model score thresholds. A model with no predictive power has an AUC of 0.5, whereas a perfect model has a score of 1.0.

hasMetricDataPoints

public final boolean hasMetricDataPoints()

Returns true if the MetricDataPoints property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty). For responses returned by the SDK, the sender is the AWS service.

metricDataPoints

public final List<MetricDataPoint> metricDataPoints()

The data points details.

Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

You can use hasMetricDataPoints() to see if a value was sent in this field.

Returns:

The data points details.

toBuilder

public TrainingMetrics.Builder toBuilder()

Specified by:

toBuilder in interface ToCopyableBuilder<TrainingMetrics.Builder,TrainingMetrics>

builder

public static TrainingMetrics.Builder builder()

serializableBuilderClass

public static Class<? extends TrainingMetrics.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