software.amazon.awssdk.services.frauddetector.model

Class LabelSchema

java.lang.Object

software.amazon.awssdk.services.frauddetector.model.LabelSchema

All Implemented Interfaces:

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

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

The label schema.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static interface	LabelSchema.Builder

Method Summary

Modifier and Type	Method and Description
static LabelSchema.Builder	builder()
boolean	equals(Object obj)
boolean	equalsBySdkFields(Object obj)
<T> Optional<T>	getValueForField(String fieldName, Class<T> clazz)
int	hashCode()
boolean	hasLabelMapper() For responses, this returns true if the service returned a value for the LabelMapper property.
Map<String,List<String>>	labelMapper() The label mapper maps the Amazon Fraud Detector supported model classification labels (FRAUD, LEGIT) to the appropriate event type labels.
List<SdkField<?>>	sdkFields()
static Class<? extends LabelSchema.Builder>	serializableBuilderClass()
LabelSchema.Builder	toBuilder()
String	toString() Returns a string representation of this object.
UnlabeledEventsTreatment	unlabeledEventsTreatment() The action to take for unlabeled events.
String	unlabeledEventsTreatmentAsString() The action to take for unlabeled events.

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

hasLabelMapper

public final boolean hasLabelMapper()

For responses, this returns true if the service returned a value for the LabelMapper property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

labelMapper

public final Map<String,List<String>> labelMapper()

The label mapper maps the Amazon Fraud Detector supported model classification labels (FRAUD, LEGIT) to the appropriate event type labels. For example, if "FRAUD" and " LEGIT" are Amazon Fraud Detector supported labels, this mapper could be: {"FRAUD" => ["0"], "LEGIT" => ["1"]} or {"FRAUD" => ["false"], "LEGIT" => ["true"]} or {"FRAUD" => ["fraud", "abuse"], "LEGIT" => ["legit", "safe"]}. The value part of the mapper is a list, because you may have multiple label variants from your event type for a single Amazon Fraud Detector label.

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

This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasLabelMapper() method.

Returns:

The label mapper maps the Amazon Fraud Detector supported model classification labels (FRAUD , LEGIT) to the appropriate event type labels. For example, if "FRAUD" and " LEGIT" are Amazon Fraud Detector supported labels, this mapper could be: {"FRAUD" => ["0"], "LEGIT" => ["1"]} or {"FRAUD" => ["false"], "LEGIT" => ["true"]} or {"FRAUD" => ["fraud", "abuse"], "LEGIT" => ["legit", "safe"]}. The value part of the mapper is a list, because you may have multiple label variants from your event type for a single Amazon Fraud Detector label.

unlabeledEventsTreatment

public final UnlabeledEventsTreatment unlabeledEventsTreatment()

The action to take for unlabeled events.

• Use IGNORE if you want the unlabeled events to be ignored. This is recommended when the majority of the events in the dataset are labeled.

• Use FRAUD if you want to categorize all unlabeled events as “Fraud”. This is recommended when most of the events in your dataset are fraudulent.

• Use LEGIT if you want to categorize all unlabeled events as “Legit”. This is recommended when most of the events in your dataset are legitimate.

• Use AUTO if you want Amazon Fraud Detector to decide how to use the unlabeled data. This is recommended when there is significant unlabeled events in the dataset.

By default, Amazon Fraud Detector ignores the unlabeled data.

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

Returns:

The action to take for unlabeled events.

• Use IGNORE if you want the unlabeled events to be ignored. This is recommended when the majority of the events in the dataset are labeled.

• Use FRAUD if you want to categorize all unlabeled events as “Fraud”. This is recommended when most of the events in your dataset are fraudulent.

• Use LEGIT if you want to categorize all unlabeled events as “Legit”. This is recommended when most of the events in your dataset are legitimate.

• Use AUTO if you want Amazon Fraud Detector to decide how to use the unlabeled data. This is recommended when there is significant unlabeled events in the dataset.

By default, Amazon Fraud Detector ignores the unlabeled data.

See Also:

UnlabeledEventsTreatment

unlabeledEventsTreatmentAsString

public final String unlabeledEventsTreatmentAsString()

The action to take for unlabeled events.

• Use IGNORE if you want the unlabeled events to be ignored. This is recommended when the majority of the events in the dataset are labeled.

• Use FRAUD if you want to categorize all unlabeled events as “Fraud”. This is recommended when most of the events in your dataset are fraudulent.

• Use LEGIT if you want to categorize all unlabeled events as “Legit”. This is recommended when most of the events in your dataset are legitimate.

• Use AUTO if you want Amazon Fraud Detector to decide how to use the unlabeled data. This is recommended when there is significant unlabeled events in the dataset.

By default, Amazon Fraud Detector ignores the unlabeled data.

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

Returns:

The action to take for unlabeled events.

• Use IGNORE if you want the unlabeled events to be ignored. This is recommended when the majority of the events in the dataset are labeled.

• Use FRAUD if you want to categorize all unlabeled events as “Fraud”. This is recommended when most of the events in your dataset are fraudulent.

• Use LEGIT if you want to categorize all unlabeled events as “Legit”. This is recommended when most of the events in your dataset are legitimate.

• Use AUTO if you want Amazon Fraud Detector to decide how to use the unlabeled data. This is recommended when there is significant unlabeled events in the dataset.

By default, Amazon Fraud Detector ignores the unlabeled data.

See Also:

UnlabeledEventsTreatment

toBuilder

public LabelSchema.Builder toBuilder()

Specified by:

toBuilder in interface ToCopyableBuilder<LabelSchema.Builder,LabelSchema>

builder

public static LabelSchema.Builder builder()

serializableBuilderClass

public static Class<? extends LabelSchema.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