types

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Types

type ATIMetricDataPoint added in v1.20.0 

type ATIMetricDataPoint struct {

	// The anomaly discovery rate. This metric quantifies the percentage of anomalies
	// that can be detected by the model at the selected score threshold. A lower score
	// threshold increases the percentage of anomalies captured by the model, but would
	// also require challenging a larger percentage of login events, leading to a
	// higher customer friction.
	Adr *float32

	// The account takeover discovery rate. This metric quantifies the percentage of
	// account compromise events that can be detected by the model at the selected
	// score threshold. This metric is only available if 50 or more entities with
	// at-least one labeled account takeover event is present in the ingested dataset.
	Atodr *float32

	// The challenge rate. This indicates the percentage of login events that the
	// model recommends to challenge such as one-time password, multi-factor
	// authentication, and investigations.
	Cr *float32

	// The model's threshold that specifies an acceptable fraud capture rate. For
	// example, a threshold of 500 means any model score 500 or above is labeled as
	// fraud.
	Threshold *float32
	// contains filtered or unexported fields
}

The Account Takeover Insights (ATI) model performance metrics data points.

type ATIModelPerformance added in v1.20.0 

type ATIModelPerformance struct {

	// The anomaly separation index (ASI) score. This metric summarizes the overall
	// ability of the model to separate anomalous activities from the normal behavior.
	// Depending on the business, a large fraction of these anomalous activities can be
	// malicious and correspond to the account takeover attacks. A model with no
	// separability power will have the lowest possible ASI score of 0.5, whereas the a
	// model with a high separability power will have the highest possible ASI score of
	// 1.0
	Asi *float32
	// contains filtered or unexported fields
}

The Account Takeover Insights (ATI) model performance score.

type ATITrainingMetricsValue added in v1.20.0 

type ATITrainingMetricsValue struct {

	// The model's performance metrics data points.
	MetricDataPoints []ATIMetricDataPoint

	// The model's overall performance scores.
	ModelPerformance *ATIModelPerformance
	// contains filtered or unexported fields
}

The Account Takeover Insights (ATI) model training metric details.

type AccessDeniedException 

type AccessDeniedException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

An exception indicating Amazon Fraud Detector does not have the needed permissions. This can occur if you submit a request, such as PutExternalModel , that specifies a role that is not in your account.

func (*AccessDeniedException) Error 

func (e *AccessDeniedException) Error() string

func (*AccessDeniedException) ErrorCode 

func (e *AccessDeniedException) ErrorCode() string

func (*AccessDeniedException) ErrorFault 

func (e *AccessDeniedException) ErrorFault() smithy.ErrorFault

func (*AccessDeniedException) ErrorMessage 

func (e *AccessDeniedException) ErrorMessage() string

type AggregatedLogOddsMetric added in v1.20.0 

type AggregatedLogOddsMetric struct {

	// The relative importance of the variables in the list to the other event
	// variable.
	//
	// This member is required.
	AggregatedVariablesImportance *float32

	// The names of all the variables.
	//
	// This member is required.
	VariableNames []string
	// contains filtered or unexported fields
}

The log odds metric details. Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might calculate the number of times an user has logged in using the same IP address. In this case, event variables used to derive the aggregated variables are IP address and user .

type AggregatedVariablesImpactExplanation added in v1.20.0 

type AggregatedVariablesImpactExplanation struct {

	// The names of all the event variables that were used to derive the aggregated
	// variables.
	EventVariableNames []string

	// The raw, uninterpreted value represented as log-odds of the fraud. These values
	// are usually between -10 to +10, but range from -infinity to +infinity.
	//   - A positive value indicates that the variables drove the risk score up.
	//   - A negative value indicates that the variables drove the risk score down.
	LogOddsImpact *float32

	// The relative impact of the aggregated variables in terms of magnitude on the
	// prediction scores.
	RelativeImpact *string
	// contains filtered or unexported fields
}

The details of the impact of aggregated variables on the prediction score. Account Takeover Insights (ATI) model uses the login data you provide to continuously calculate a set of variables (aggregated variables) based on historical events. For example, the model might calculate the number of times an user has logged in using the same IP address. In this case, event variables used to derive the aggregated variables are IP address and user .

type AggregatedVariablesImportanceMetrics added in v1.20.0 

type AggregatedVariablesImportanceMetrics struct {

	// List of variables' metrics.
	LogOddsMetrics []AggregatedLogOddsMetric
	// contains filtered or unexported fields
}

The details of the relative importance of the aggregated variables. Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might calculate the number of times an user has logged in using the same IP address. In this case, event variables used to derive the aggregated variables are IP address and user .

type AllowDenyList added in v1.23.0 

type AllowDenyList struct {

	// The name of the list.
	//
	// This member is required.
	Name *string

	// The ARN of the list.
	Arn *string

	// The time the list was created.
	CreatedTime *string

	// The description of the list.
	Description *string

	// The time the list was last updated.
	UpdatedTime *string

	// The variable type of the list.
	VariableType *string
	// contains filtered or unexported fields
}

The metadata of a list.

type AsyncJobStatus added in v1.3.0 

type AsyncJobStatus string
const (
	AsyncJobStatusInProgressInitializing AsyncJobStatus = "IN_PROGRESS_INITIALIZING"
	AsyncJobStatusInProgress             AsyncJobStatus = "IN_PROGRESS"
	AsyncJobStatusCancelInProgress       AsyncJobStatus = "CANCEL_IN_PROGRESS"
	AsyncJobStatusCanceled               AsyncJobStatus = "CANCELED"
	AsyncJobStatusComplete               AsyncJobStatus = "COMPLETE"
	AsyncJobStatusFailed                 AsyncJobStatus = "FAILED"
)

Enum values for AsyncJobStatus

func (AsyncJobStatus) Values added in v1.3.0 

func (AsyncJobStatus) Values() []AsyncJobStatus

Values returns all known values for AsyncJobStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type BatchCreateVariableError 

type BatchCreateVariableError struct {

	// The error code.
	Code int32

	// The error message.
	Message *string

	// The name.
	Name *string
	// contains filtered or unexported fields
}

Provides the error of the batch create variable API.

type BatchGetVariableError 

type BatchGetVariableError struct {

	// The error code.
	Code int32

	// The error message.
	Message *string

	// The error name.
	Name *string
	// contains filtered or unexported fields
}

Provides the error of the batch get variable API.

type BatchImport added in v1.10.0 

type BatchImport struct {

	// The ARN of the batch import job.
	Arn *string

	// Timestamp of when batch import job completed.
	CompletionTime *string

	// The name of the event type.
	EventTypeName *string

	// The number of records that failed to import.
	FailedRecordsCount *int32

	// The reason batch import job failed.
	FailureReason *string

	// The ARN of the IAM role to use for this job request.
	IamRoleArn *string

	// The Amazon S3 location of your data file for batch import.
	InputPath *string

	// The ID of the batch import job.
	JobId *string

	// The Amazon S3 location of your output file.
	OutputPath *string

	// The number of records processed by batch import job.
	ProcessedRecordsCount *int32

	// Timestamp of when the batch import job started.
	StartTime *string

	// The status of the batch import job.
	Status AsyncJobStatus

	// The total number of records in the batch import job.
	TotalRecordsCount *int32
	// contains filtered or unexported fields
}

The batch import job details.

type BatchPrediction added in v1.3.0 

type BatchPrediction struct {

	// The ARN of batch prediction job.
	Arn *string

	// Timestamp of when the batch prediction job completed.
	CompletionTime *string

	// The name of the detector.
	DetectorName *string

	// The detector version.
	DetectorVersion *string

	// The name of the event type.
	EventTypeName *string

	// The reason a batch prediction job failed.
	FailureReason *string

	// The ARN of the IAM role to use for this job request.
	IamRoleArn *string

	// The Amazon S3 location of your training file.
	InputPath *string

	// The job ID for the batch prediction.
	JobId *string

	// Timestamp of most recent heartbeat indicating the batch prediction job was
	// making progress.
	LastHeartbeatTime *string

	// The Amazon S3 location of your output file.
	OutputPath *string

	// The number of records processed by the batch prediction job.
	ProcessedRecordsCount *int32

	// Timestamp of when the batch prediction job started.
	StartTime *string

	// The batch prediction status.
	Status AsyncJobStatus

	// The total number of records in the batch prediction job.
	TotalRecordsCount *int32
	// contains filtered or unexported fields
}

The batch prediction details.

type ConflictException 

type ConflictException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

An exception indicating there was a conflict during a delete operation.

func (*ConflictException) Error 

func (e *ConflictException) Error() string

func (*ConflictException) ErrorCode 

func (e *ConflictException) ErrorCode() string

func (*ConflictException) ErrorFault 

func (e *ConflictException) ErrorFault() smithy.ErrorFault

func (*ConflictException) ErrorMessage 

func (e *ConflictException) ErrorMessage() string

type DataSource 

type DataSource string
const (
	DataSourceEvent              DataSource = "EVENT"
	DataSourceModelScore         DataSource = "MODEL_SCORE"
	DataSourceExternalModelScore DataSource = "EXTERNAL_MODEL_SCORE"
)

Enum values for DataSource

func (DataSource) Values added in v0.29.0 

func (DataSource) Values() []DataSource

Values returns all known values for DataSource. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type DataType 

type DataType string
const (
	DataTypeString   DataType = "STRING"
	DataTypeInteger  DataType = "INTEGER"
	DataTypeFloat    DataType = "FLOAT"
	DataTypeBoolean  DataType = "BOOLEAN"
	DataTypeDatetime DataType = "DATETIME"
)

Enum values for DataType

func (DataType) Values added in v0.29.0 

func (DataType) Values() []DataType

Values returns all known values for DataType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type DataValidationMetrics 

type DataValidationMetrics struct {

	// The field-specific model training validation messages.
	FieldLevelMessages []FieldValidationMessage

	// The file-specific model training data validation messages.
	FileLevelMessages []FileValidationMessage
	// contains filtered or unexported fields
}

The model training data validation metrics.

type Detector 

type Detector struct {

	// The detector ARN.
	Arn *string

	// Timestamp of when the detector was created.
	CreatedTime *string

	// The detector description.
	Description *string

	// The detector ID.
	DetectorId *string

	// The name of the event type.
	EventTypeName *string

	// Timestamp of when the detector was last updated.
	LastUpdatedTime *string
	// contains filtered or unexported fields
}

The detector.

type DetectorVersionStatus 

type DetectorVersionStatus string
const (
	DetectorVersionStatusDraft    DetectorVersionStatus = "DRAFT"
	DetectorVersionStatusActive   DetectorVersionStatus = "ACTIVE"
	DetectorVersionStatusInactive DetectorVersionStatus = "INACTIVE"
)

Enum values for DetectorVersionStatus

func (DetectorVersionStatus) Values added in v0.29.0 

func (DetectorVersionStatus) Values() []DetectorVersionStatus

Values returns all known values for DetectorVersionStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type DetectorVersionSummary 

type DetectorVersionSummary struct {

	// The detector version description.
	Description *string

	// The detector version ID.
	DetectorVersionId *string

	// Timestamp of when the detector version was last updated.
	LastUpdatedTime *string

	// The detector version status.
	Status DetectorVersionStatus
	// contains filtered or unexported fields
}

The summary of the detector version.

type Entity 

type Entity struct {

	// The entity ID. If you do not know the entityId , you can pass unknown , which is
	// areserved string literal.
	//
	// This member is required.
	EntityId *string

	// The entity type.
	//
	// This member is required.
	EntityType *string
	// contains filtered or unexported fields
}

The entity details.

type EntityType 

type EntityType struct {

	// The entity type ARN.
	Arn *string

	// Timestamp of when the entity type was created.
	CreatedTime *string

	// The entity type description.
	Description *string

	// Timestamp of when the entity type was last updated.
	LastUpdatedTime *string

	// The entity type name.
	Name *string
	// contains filtered or unexported fields
}

The entity type details.

type EvaluatedExternalModel added in v1.17.0 

type EvaluatedExternalModel struct {

	// Input variables use for generating predictions.
	InputVariables map[string]string

	// The endpoint of the external (Amazon Sagemaker) model.
	ModelEndpoint *string

	// Output variables.
	OutputVariables map[string]string

	// Indicates whether event variables were used to generate predictions.
	UseEventVariables *bool
	// contains filtered or unexported fields
}

The details of the external (Amazon Sagemaker) model evaluated for generating predictions.

type EvaluatedModelVersion added in v1.17.0 

type EvaluatedModelVersion struct {

	// Evaluations generated for the model version.
	Evaluations []ModelVersionEvaluation

	// The model ID.
	ModelId *string

	// The model type. Valid values: ONLINE_FRAUD_INSIGHTS | TRANSACTION_FRAUD_INSIGHTS
	ModelType *string

	// The model version.
	ModelVersion *string
	// contains filtered or unexported fields
}

The model version evaluated for generating prediction.

type EvaluatedRule added in v1.17.0 

type EvaluatedRule struct {

	// Indicates whether the rule was evaluated.
	Evaluated *bool

	// The rule expression.
	Expression *string

	// The rule expression value.
	ExpressionWithValues *string

	// Indicates whether the rule matched.
	Matched *bool

	// The rule outcome.
	Outcomes []string

	// The rule ID.
	RuleId *string

	// The rule version.
	RuleVersion *string
	// contains filtered or unexported fields
}

The details of the rule used for evaluating variable values.

type Event added in v1.10.0 

type Event struct {

	// The label associated with the event.
	CurrentLabel *string

	// The event entities.
	Entities []Entity

	// The event ID.
	EventId *string

	// The timestamp that defines when the event under evaluation occurred. The
	// timestamp must be specified using ISO 8601 standard in UTC.
	EventTimestamp *string

	// The event type.
	EventTypeName *string

	// Names of the event type's variables you defined in Amazon Fraud Detector to
	// represent data elements and their corresponding values for the event you are
	// sending for evaluation.
	EventVariables map[string]string

	// The timestamp associated with the label to update. The timestamp must be
	// specified using ISO 8601 standard in UTC.
	LabelTimestamp *string
	// contains filtered or unexported fields
}

The event details.

type EventIngestion added in v1.10.0 

type EventIngestion string
const (
	EventIngestionEnabled  EventIngestion = "ENABLED"
	EventIngestionDisabled EventIngestion = "DISABLED"
)

Enum values for EventIngestion

func (EventIngestion) Values added in v1.10.0 

func (EventIngestion) Values() []EventIngestion

Values returns all known values for EventIngestion. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type EventOrchestration added in v1.24.0 

type EventOrchestration struct {

	// Specifies if event orchestration is enabled through Amazon EventBridge.
	//
	// This member is required.
	EventBridgeEnabled *bool
	// contains filtered or unexported fields
}

The event orchestration status.

type EventPredictionSummary added in v1.17.0 

type EventPredictionSummary struct {

	// The detector ID.
	DetectorId *string

	// The detector version ID.
	DetectorVersionId *string

	// The event ID.
	EventId *string

	// The timestamp of the event.
	EventTimestamp *string

	// The event type.
	EventTypeName *string

	// The timestamp when the prediction was generated.
	PredictionTimestamp *string
	// contains filtered or unexported fields
}

Information about the summary of an event prediction.

type EventType 

type EventType struct {

	// The entity type ARN.
	Arn *string

	// Timestamp of when the event type was created.
	CreatedTime *string

	// The event type description.
	Description *string

	// The event type entity types.
	EntityTypes []string

	// If Enabled , Amazon Fraud Detector stores event data when you generate a
	// prediction and uses that data to update calculated variables in near real-time.
	// Amazon Fraud Detector uses this data, known as INGESTED_EVENTS , to train your
	// model and improve fraud predictions.
	EventIngestion EventIngestion

	// The event orchestration status.
	EventOrchestration *EventOrchestration

	// The event type event variables.
	EventVariables []string

	// Data about the stored events.
	IngestedEventStatistics *IngestedEventStatistics

	// The event type labels.
	Labels []string

	// Timestamp of when the event type was last updated.
	LastUpdatedTime *string

	// The event type name.
	Name *string
	// contains filtered or unexported fields
}

The event type details.

type EventVariableSummary added in v1.17.0 

type EventVariableSummary struct {

	// The event variable name.
	Name *string

	// The event variable source.
	Source *string

	// The value of the event variable.
	Value *string
	// contains filtered or unexported fields
}

Information about the summary of an event variable that was evaluated for generating prediction.

type ExternalEventsDetail 

type ExternalEventsDetail struct {

	// The ARN of the role that provides Amazon Fraud Detector access to the data
	// location.
	//
	// This member is required.
	DataAccessRoleArn *string

	// The Amazon S3 bucket location for the data.
	//
	// This member is required.
	DataLocation *string
	// contains filtered or unexported fields
}

Details for the external events data used for model version training.

type ExternalModel 

type ExternalModel struct {

	// The model ARN.
	Arn *string

	// Timestamp of when the model was last created.
	CreatedTime *string

	// The input configuration.
	InputConfiguration *ModelInputConfiguration

	// The role used to invoke the model.
	InvokeModelEndpointRoleArn *string

	// Timestamp of when the model was last updated.
	LastUpdatedTime *string

	// The Amazon SageMaker model endpoints.
	ModelEndpoint *string

	// The Amazon Fraud Detector status for the external model endpoint
	ModelEndpointStatus ModelEndpointStatus

	// The source of the model.
	ModelSource ModelSource

	// The output configuration.
	OutputConfiguration *ModelOutputConfiguration
	// contains filtered or unexported fields
}

The Amazon SageMaker model.

type ExternalModelOutputs added in v1.9.0 

type ExternalModelOutputs struct {

	// The Amazon SageMaker model.
	ExternalModel *ExternalModelSummary

	// The fraud prediction scores from Amazon SageMaker model.
	Outputs map[string]string
	// contains filtered or unexported fields
}

The fraud prediction scores from Amazon SageMaker model.

type ExternalModelSummary added in v1.9.0 

type ExternalModelSummary struct {

	// The endpoint of the Amazon SageMaker model.
	ModelEndpoint *string

	// The source of the model.
	ModelSource ModelSource
	// contains filtered or unexported fields
}

The Amazon SageMaker model.

type FieldValidationMessage 

type FieldValidationMessage struct {

	// The message content.
	Content *string

	// The field name.
	FieldName *string

	// The message ID.
	Identifier *string

	// The message title.
	Title *string

	// The message type.
	Type *string
	// contains filtered or unexported fields
}

The message details.

type FileValidationMessage 

type FileValidationMessage struct {

	// The message content.
	Content *string

	// The message title.
	Title *string

	// The message type.
	Type *string
	// contains filtered or unexported fields
}

The message details.

type FilterCondition added in v1.17.0 

type FilterCondition struct {

	// A statement containing a resource property and a value to specify filter
	// condition.
	Value *string
	// contains filtered or unexported fields
}

A conditional statement for filtering a list of past predictions.

type IngestedEventStatistics added in v1.10.0 

type IngestedEventStatistics struct {

	// The total size of the stored events.
	EventDataSizeInBytes *int64

	// Timestamp of when the stored event was last updated.
	LastUpdatedTime *string

	// The oldest stored event.
	LeastRecentEvent *string

	// The newest stored event.
	MostRecentEvent *string

	// The number of stored events.
	NumberOfEvents *int64
	// contains filtered or unexported fields
}

Data about the stored events.

type IngestedEventsDetail added in v1.10.0 

type IngestedEventsDetail struct {

	// The start and stop time of the ingested events.
	//
	// This member is required.
	IngestedEventsTimeWindow *IngestedEventsTimeWindow
	// contains filtered or unexported fields
}

The details of the ingested event.

type IngestedEventsTimeWindow added in v1.10.0 

type IngestedEventsTimeWindow struct {

	// Timestamp of the final ingested event.
	//
	// This member is required.
	EndTime *string

	// Timestamp of the first ingensted event.
	//
	// This member is required.
	StartTime *string
	// contains filtered or unexported fields
}

The start and stop time of the ingested events.

type InternalServerException 

type InternalServerException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

An exception indicating an internal server error.

func (*InternalServerException) Error 

func (e *InternalServerException) Error() string

func (*InternalServerException) ErrorCode 

func (e *InternalServerException) ErrorCode() string

func (*InternalServerException) ErrorFault 

func (e *InternalServerException) ErrorFault() smithy.ErrorFault

func (*InternalServerException) ErrorMessage 

func (e *InternalServerException) ErrorMessage() string

type KMSKey 

type KMSKey struct {

	// The encryption key ARN.
	KmsEncryptionKeyArn *string
	// contains filtered or unexported fields
}

The KMS key details.

type Label 

type Label struct {

	// The label ARN.
	Arn *string

	// Timestamp of when the event type was created.
	CreatedTime *string

	// The label description.
	Description *string

	// Timestamp of when the label was last updated.
	LastUpdatedTime *string

	// The label name.
	Name *string
	// contains filtered or unexported fields
}

The label details.

type LabelSchema 

type LabelSchema struct {

	// 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.
	LabelMapper map[string][]string

	// 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.
	UnlabeledEventsTreatment UnlabeledEventsTreatment
	// contains filtered or unexported fields
}

The label schema.

type Language 

type Language string
const (
	LanguageDetectorpl Language = "DETECTORPL"
)

Enum values for Language

func (Language) Values added in v0.29.0 

func (Language) Values() []Language

Values returns all known values for Language. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ListUpdateMode added in v1.23.0 

type ListUpdateMode string
const (
	ListUpdateModeReplace ListUpdateMode = "REPLACE"
	ListUpdateModeAppend  ListUpdateMode = "APPEND"
	ListUpdateModeRemove  ListUpdateMode = "REMOVE"
)

Enum values for ListUpdateMode

func (ListUpdateMode) Values added in v1.23.0 

func (ListUpdateMode) Values() []ListUpdateMode

Values returns all known values for ListUpdateMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type LogOddsMetric added in v1.7.0 

type LogOddsMetric struct {

	// The relative importance of the variable. For more information, see Model
	// variable importance (https://docs.aws.amazon.com/frauddetector/latest/ug/model-variable-importance.html)
	// .
	//
	// This member is required.
	VariableImportance *float32

	// The name of the variable.
	//
	// This member is required.
	VariableName *string

	// The type of variable.
	//
	// This member is required.
	VariableType *string
	// contains filtered or unexported fields
}

The log odds metric details.

type MetricDataPoint 

type MetricDataPoint struct {

	// The false positive rate. This is the percentage of total legitimate events that
	// are incorrectly predicted as fraud.
	Fpr *float32

	// The percentage of fraud events correctly predicted as fraudulent as compared to
	// all events predicted as fraudulent.
	Precision *float32

	// The model threshold that specifies an acceptable fraud capture rate. For
	// example, a threshold of 500 means any model score 500 or above is labeled as
	// fraud.
	Threshold *float32

	// The true positive rate. This is the percentage of total fraud the model
	// detects. Also known as capture rate.
	Tpr *float32
	// contains filtered or unexported fields
}

Model performance metrics data points.

type Model 

type Model struct {

	// The ARN of the model.
	Arn *string

	// Timestamp of when the model was created.
	CreatedTime *string

	// The model description.
	Description *string

	// The name of the event type.
	EventTypeName *string

	// Timestamp of last time the model was updated.
	LastUpdatedTime *string

	// The model ID.
	ModelId *string

	// The model type.
	ModelType ModelTypeEnum
	// contains filtered or unexported fields
}

The model.

type ModelEndpointDataBlob 

type ModelEndpointDataBlob struct {

	// The byte buffer of the Amazon SageMaker model endpoint input data blob.
	ByteBuffer []byte

	// The content type of the Amazon SageMaker model endpoint input data blob.
	ContentType *string
	// contains filtered or unexported fields
}

A pre-formed Amazon SageMaker model input you can include if your detector version includes an imported Amazon SageMaker model endpoint with pass-through input configuration.

type ModelEndpointStatus 

type ModelEndpointStatus string
const (
	ModelEndpointStatusAssociated  ModelEndpointStatus = "ASSOCIATED"
	ModelEndpointStatusDissociated ModelEndpointStatus = "DISSOCIATED"
)

Enum values for ModelEndpointStatus

func (ModelEndpointStatus) Values added in v0.29.0 

func (ModelEndpointStatus) Values() []ModelEndpointStatus

Values returns all known values for ModelEndpointStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ModelInputConfiguration 

type ModelInputConfiguration struct {

	// The event variables.
	//
	// This member is required.
	UseEventVariables *bool

	// Template for constructing the CSV input-data sent to SageMaker. At
	// event-evaluation, the placeholders for variable-names in the template will be
	// replaced with the variable values before being sent to SageMaker.
	CsvInputTemplate *string

	// The event type name.
	EventTypeName *string

	// The format of the model input configuration. The format differs depending on if
	// it is passed through to SageMaker or constructed by Amazon Fraud Detector.
	Format ModelInputDataFormat

	// Template for constructing the JSON input-data sent to SageMaker. At
	// event-evaluation, the placeholders for variable names in the template will be
	// replaced with the variable values before being sent to SageMaker.
	JsonInputTemplate *string
	// contains filtered or unexported fields
}

The Amazon SageMaker model input configuration.

type ModelInputDataFormat 

type ModelInputDataFormat string
const (
	ModelInputDataFormatCsv  ModelInputDataFormat = "TEXT_CSV"
	ModelInputDataFormatJson ModelInputDataFormat = "APPLICATION_JSON"
)

Enum values for ModelInputDataFormat

func (ModelInputDataFormat) Values added in v0.29.0 

func (ModelInputDataFormat) Values() []ModelInputDataFormat

Values returns all known values for ModelInputDataFormat. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ModelOutputConfiguration 

type ModelOutputConfiguration struct {

	// The format of the model output configuration.
	//
	// This member is required.
	Format ModelOutputDataFormat

	// A map of CSV index values in the SageMaker response to the Amazon Fraud
	// Detector variables.
	CsvIndexToVariableMap map[string]string

	// A map of JSON keys in response from SageMaker to the Amazon Fraud Detector
	// variables.
	JsonKeyToVariableMap map[string]string
	// contains filtered or unexported fields
}

Provides the Amazon Sagemaker model output configuration.

type ModelOutputDataFormat 

type ModelOutputDataFormat string
const (
	ModelOutputDataFormatCsv       ModelOutputDataFormat = "TEXT_CSV"
	ModelOutputDataFormatJsonlines ModelOutputDataFormat = "APPLICATION_JSONLINES"
)

Enum values for ModelOutputDataFormat

func (ModelOutputDataFormat) Values added in v0.29.0 

func (ModelOutputDataFormat) Values() []ModelOutputDataFormat

Values returns all known values for ModelOutputDataFormat. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ModelScores 

type ModelScores struct {

	// The model version.
	ModelVersion *ModelVersion

	// The model's fraud prediction scores.
	Scores map[string]float32
	// contains filtered or unexported fields
}

The fraud prediction scores.

type ModelSource 

type ModelSource string
const (
	ModelSourceSagemaker ModelSource = "SAGEMAKER"
)

Enum values for ModelSource

func (ModelSource) Values added in v0.29.0 

func (ModelSource) Values() []ModelSource

Values returns all known values for ModelSource. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ModelTypeEnum 

type ModelTypeEnum string
const (
	ModelTypeEnumOnlineFraudInsights      ModelTypeEnum = "ONLINE_FRAUD_INSIGHTS"
	ModelTypeEnumTransactionFraudInsights ModelTypeEnum = "TRANSACTION_FRAUD_INSIGHTS"
	ModelTypeEnumAccountTakeoverInsights  ModelTypeEnum = "ACCOUNT_TAKEOVER_INSIGHTS"
)

Enum values for ModelTypeEnum

func (ModelTypeEnum) Values added in v0.29.0 

func (ModelTypeEnum) Values() []ModelTypeEnum

Values returns all known values for ModelTypeEnum. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ModelVersion 

type ModelVersion struct {

	// The model ID.
	//
	// This member is required.
	ModelId *string

	// The model type.
	//
	// This member is required.
	ModelType ModelTypeEnum

	// The model version number.
	//
	// This member is required.
	ModelVersionNumber *string

	// The model version ARN.
	Arn *string
	// contains filtered or unexported fields
}

The model version.

type ModelVersionDetail 

type ModelVersionDetail struct {

	// The model version ARN.
	Arn *string

	// The timestamp when the model was created.
	CreatedTime *string

	// The external events data details. This will be populated if the
	// trainingDataSource for the model version is specified as EXTERNAL_EVENTS .
	ExternalEventsDetail *ExternalEventsDetail

	// The ingested events data details. This will be populated if the
	// trainingDataSource for the model version is specified as INGESTED_EVENTS .
	IngestedEventsDetail *IngestedEventsDetail

	// The timestamp when the model was last updated.
	LastUpdatedTime *string

	// The model ID.
	ModelId *string

	// The model type.
	ModelType ModelTypeEnum

	// The model version number.
	ModelVersionNumber *string

	// The status of the model version.
	Status *string

	// The training data schema.
	TrainingDataSchema *TrainingDataSchema

	// The model version training data source.
	TrainingDataSource TrainingDataSourceEnum

	// The training results.
	TrainingResult *TrainingResult

	// The training result details. The details include the relative importance of the
	// variables.
	TrainingResultV2 *TrainingResultV2
	// contains filtered or unexported fields
}

The details of the model version.

type ModelVersionEvaluation added in v1.17.0 

type ModelVersionEvaluation struct {

	// The evaluation score generated for the model version.
	EvaluationScore *string

	// The output variable name.
	OutputVariableName *string

	// The prediction explanations generated for the model version.
	PredictionExplanations *PredictionExplanations
	// contains filtered or unexported fields
}

The model version evalutions.

type ModelVersionStatus 

type ModelVersionStatus string
const (
	ModelVersionStatusActive            ModelVersionStatus = "ACTIVE"
	ModelVersionStatusInactive          ModelVersionStatus = "INACTIVE"
	ModelVersionStatusTrainingCancelled ModelVersionStatus = "TRAINING_CANCELLED"
)

Enum values for ModelVersionStatus

func (ModelVersionStatus) Values added in v0.29.0 

func (ModelVersionStatus) Values() []ModelVersionStatus

Values returns all known values for ModelVersionStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type OFIMetricDataPoint added in v1.20.0 

type OFIMetricDataPoint struct {

	// The false positive rate. This is the percentage of total legitimate events that
	// are incorrectly predicted as fraud.
	Fpr *float32

	// The percentage of fraud events correctly predicted as fraudulent as compared to
	// all events predicted as fraudulent.
	Precision *float32

	// The model threshold that specifies an acceptable fraud capture rate. For
	// example, a threshold of 500 means any model score 500 or above is labeled as
	// fraud.
	Threshold *float32

	// The true positive rate. This is the percentage of total fraud the model
	// detects. Also known as capture rate.
	Tpr *float32
	// contains filtered or unexported fields
}

The Online Fraud Insights (OFI) model performance metrics data points.

type OFIModelPerformance added in v1.20.0 

type OFIModelPerformance struct {

	// The area under the curve (auc). This summarizes the total positive rate (tpr)
	// and false positive rate (FPR) across all possible model score thresholds.
	Auc *float32

	// Indicates the range of area under curve (auc) expected from the OFI model. A
	// range greater than 0.1 indicates higher model uncertainity.
	UncertaintyRange *UncertaintyRange
	// contains filtered or unexported fields
}

The Online Fraud Insights (OFI) model performance score.

type OFITrainingMetricsValue added in v1.20.0 

type OFITrainingMetricsValue struct {

	// The model's performance metrics data points.
	MetricDataPoints []OFIMetricDataPoint

	// The model's overall performance score.
	ModelPerformance *OFIModelPerformance
	// contains filtered or unexported fields
}

The Online Fraud Insights (OFI) model training metric details.

type Outcome 

type Outcome struct {

	// The outcome ARN.
	Arn *string

	// The timestamp when the outcome was created.
	CreatedTime *string

	// The outcome description.
	Description *string

	// The timestamp when the outcome was last updated.
	LastUpdatedTime *string

	// The outcome name.
	Name *string
	// contains filtered or unexported fields
}

The outcome.

type PredictionExplanations added in v1.17.0 

type PredictionExplanations struct {

	// The details of the aggregated variables impact on the prediction score. Account
	// Takeover Insights (ATI) model uses event variables from the login data you
	// provide to continuously calculate a set of variables (aggregated variables)
	// based on historical events. For example, your ATI model might calculate the
	// number of times an user has logged in using the same IP address. In this case,
	// event variables used to derive the aggregated variables are IP address and user .
	AggregatedVariablesImpactExplanations []AggregatedVariablesImpactExplanation

	// The details of the event variable's impact on the prediction score.
	VariableImpactExplanations []VariableImpactExplanation
	// contains filtered or unexported fields
}

The prediction explanations that provide insight into how each event variable impacted the model version's fraud prediction score.

type PredictionTimeRange added in v1.17.0 

type PredictionTimeRange struct {

	// The end time of the time period for when the predictions were generated.
	//
	// This member is required.
	EndTime *string

	// The start time of the time period for when the predictions were generated.
	//
	// This member is required.
	StartTime *string
	// contains filtered or unexported fields
}

The time period for when the predictions were generated.

type ResourceNotFoundException 

type ResourceNotFoundException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

An exception indicating the specified resource was not found.

func (*ResourceNotFoundException) Error 

func (e *ResourceNotFoundException) Error() string

func (*ResourceNotFoundException) ErrorCode 

func (e *ResourceNotFoundException) ErrorCode() string

func (*ResourceNotFoundException) ErrorFault 

func (e *ResourceNotFoundException) ErrorFault() smithy.ErrorFault

func (*ResourceNotFoundException) ErrorMessage 

func (e *ResourceNotFoundException) ErrorMessage() string

type ResourceUnavailableException added in v1.7.0 

type ResourceUnavailableException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

An exception indicating that the attached customer-owned (external) model threw an exception when Amazon Fraud Detector invoked the model.

func (*ResourceUnavailableException) Error added in v1.7.0 

func (e *ResourceUnavailableException) Error() string

func (*ResourceUnavailableException) ErrorCode added in v1.7.0 

func (e *ResourceUnavailableException) ErrorCode() string

func (*ResourceUnavailableException) ErrorFault added in v1.7.0 

func (e *ResourceUnavailableException) ErrorFault() smithy.ErrorFault

func (*ResourceUnavailableException) ErrorMessage added in v1.7.0 

func (e *ResourceUnavailableException) ErrorMessage() string

type Rule 

type Rule struct {

	// The detector for which the rule is associated.
	//
	// This member is required.
	DetectorId *string

	// The rule ID.
	//
	// This member is required.
	RuleId *string

	// The rule version.
	//
	// This member is required.
	RuleVersion *string
	// contains filtered or unexported fields
}

A rule.

type RuleDetail 

type RuleDetail struct {

	// The rule ARN.
	Arn *string

	// The timestamp of when the rule was created.
	CreatedTime *string

	// The rule description.
	Description *string

	// The detector for which the rule is associated.
	DetectorId *string

	// The rule expression.
	Expression *string

	// The rule language.
	Language Language

	// Timestamp of the last time the rule was updated.
	LastUpdatedTime *string

	// The rule outcomes.
	Outcomes []string

	// The rule ID.
	RuleId *string

	// The rule version.
	RuleVersion *string
	// contains filtered or unexported fields
}

The details of the rule.

type RuleExecutionMode 

type RuleExecutionMode string
const (
	RuleExecutionModeAllMatched   RuleExecutionMode = "ALL_MATCHED"
	RuleExecutionModeFirstMatched RuleExecutionMode = "FIRST_MATCHED"
)

Enum values for RuleExecutionMode

func (RuleExecutionMode) Values added in v0.29.0 

func (RuleExecutionMode) Values() []RuleExecutionMode

Values returns all known values for RuleExecutionMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type RuleResult 

type RuleResult struct {

	// The outcomes of the matched rule, based on the rule execution mode.
	Outcomes []string

	// The rule ID that was matched, based on the rule execution mode.
	RuleId *string
	// contains filtered or unexported fields
}

The rule results.

type TFIMetricDataPoint added in v1.20.0 

type TFIMetricDataPoint struct {

	// The false positive rate. This is the percentage of total legitimate events that
	// are incorrectly predicted as fraud.
	Fpr *float32

	// The percentage of fraud events correctly predicted as fraudulent as compared to
	// all events predicted as fraudulent.
	Precision *float32

	// The model threshold that specifies an acceptable fraud capture rate. For
	// example, a threshold of 500 means any model score 500 or above is labeled as
	// fraud.
	Threshold *float32

	// The true positive rate. This is the percentage of total fraud the model
	// detects. Also known as capture rate.
	Tpr *float32
	// contains filtered or unexported fields
}

The performance metrics data points for Transaction Fraud Insights (TFI) model.

type TFIModelPerformance added in v1.20.0 

type TFIModelPerformance struct {

	// The area under the curve (auc). This summarizes the total positive rate (tpr)
	// and false positive rate (FPR) across all possible model score thresholds.
	Auc *float32

	// Indicates the range of area under curve (auc) expected from the TFI model. A
	// range greater than 0.1 indicates higher model uncertainity.
	UncertaintyRange *UncertaintyRange
	// contains filtered or unexported fields
}

The Transaction Fraud Insights (TFI) model performance score.

type TFITrainingMetricsValue added in v1.20.0 

type TFITrainingMetricsValue struct {

	// The model's performance metrics data points.
	MetricDataPoints []TFIMetricDataPoint

	// The model performance score.
	ModelPerformance *TFIModelPerformance
	// contains filtered or unexported fields
}

The Transaction Fraud Insights (TFI) model training metric details.

type Tag 

type Tag struct {

	// A tag key.
	//
	// This member is required.
	Key *string

	// A value assigned to a tag key.
	//
	// This member is required.
	Value *string
	// contains filtered or unexported fields
}

A key and value pair.

type ThrottlingException 

type ThrottlingException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

An exception indicating a throttling error.

func (*ThrottlingException) Error 

func (e *ThrottlingException) Error() string

func (*ThrottlingException) ErrorCode 

func (e *ThrottlingException) ErrorCode() string

func (*ThrottlingException) ErrorFault 

func (e *ThrottlingException) ErrorFault() smithy.ErrorFault

func (*ThrottlingException) ErrorMessage 

func (e *ThrottlingException) ErrorMessage() string

type TrainingDataSchema 

type TrainingDataSchema struct {

	// The training data schema variables.
	//
	// This member is required.
	ModelVariables []string

	// The label schema.
	LabelSchema *LabelSchema
	// contains filtered or unexported fields
}

The training data schema.

type TrainingDataSourceEnum 

type TrainingDataSourceEnum string
const (
	TrainingDataSourceEnumExternalEvents TrainingDataSourceEnum = "EXTERNAL_EVENTS"
	TrainingDataSourceEnumIngestedEvents TrainingDataSourceEnum = "INGESTED_EVENTS"
)

Enum values for TrainingDataSourceEnum

func (TrainingDataSourceEnum) Values added in v0.29.0 

func (TrainingDataSourceEnum) Values() []TrainingDataSourceEnum

Values returns all known values for TrainingDataSourceEnum. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TrainingMetrics 

type TrainingMetrics struct {

	// 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.
	Auc *float32

	// The data points details.
	MetricDataPoints []MetricDataPoint
	// contains filtered or unexported fields
}

The training metric details.

type TrainingMetricsV2 added in v1.20.0 

type TrainingMetricsV2 struct {

	// The Account Takeover Insights (ATI) model training metric details.
	Ati *ATITrainingMetricsValue

	// The Online Fraud Insights (OFI) model training metric details.
	Ofi *OFITrainingMetricsValue

	// The Transaction Fraud Insights (TFI) model training metric details.
	Tfi *TFITrainingMetricsValue
	// contains filtered or unexported fields
}

The training metrics details.

type TrainingResult 

type TrainingResult struct {

	// The validation metrics.
	DataValidationMetrics *DataValidationMetrics

	// The training metric details.
	TrainingMetrics *TrainingMetrics

	// The variable importance metrics.
	VariableImportanceMetrics *VariableImportanceMetrics
	// contains filtered or unexported fields
}

The training result details.

type TrainingResultV2 added in v1.20.0 

type TrainingResultV2 struct {

	// The variable importance metrics of the aggregated variables. Account Takeover
	// Insights (ATI) model uses event variables from the login data you provide to
	// continuously calculate a set of variables (aggregated variables) based on
	// historical events. For example, your ATI model might calculate the number of
	// times an user has logged in using the same IP address. In this case, event
	// variables used to derive the aggregated variables are IP address and user .
	AggregatedVariablesImportanceMetrics *AggregatedVariablesImportanceMetrics

	// The model training data validation metrics.
	DataValidationMetrics *DataValidationMetrics

	// The training metric details.
	TrainingMetricsV2 *TrainingMetricsV2

	// The variable importance metrics details.
	VariableImportanceMetrics *VariableImportanceMetrics
	// contains filtered or unexported fields
}

The training result details.

type UncertaintyRange added in v1.22.0 

type UncertaintyRange struct {

	// The lower bound value of the area under curve (auc).
	//
	// This member is required.
	LowerBoundValue *float32

	// The upper bound value of the area under curve (auc).
	//
	// This member is required.
	UpperBoundValue *float32
	// contains filtered or unexported fields
}

Range of area under curve (auc) expected from the model. A range greater than 0.1 indicates higher model uncertainity. A range is the difference between upper and lower bound of auc.

type UnlabeledEventsTreatment added in v1.10.0 

type UnlabeledEventsTreatment string
const (
	UnlabeledEventsTreatmentIgnore UnlabeledEventsTreatment = "IGNORE"
	UnlabeledEventsTreatmentFraud  UnlabeledEventsTreatment = "FRAUD"
	UnlabeledEventsTreatmentLegit  UnlabeledEventsTreatment = "LEGIT"
	UnlabeledEventsTreatmentAuto   UnlabeledEventsTreatment = "AUTO"
)

Enum values for UnlabeledEventsTreatment

func (UnlabeledEventsTreatment) Values added in v1.10.0 

func (UnlabeledEventsTreatment) Values() []UnlabeledEventsTreatment

Values returns all known values for UnlabeledEventsTreatment. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ValidationException 

type ValidationException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

An exception indicating a specified value is not allowed.

func (*ValidationException) Error 

func (e *ValidationException) Error() string

func (*ValidationException) ErrorCode 

func (e *ValidationException) ErrorCode() string

func (*ValidationException) ErrorFault 

func (e *ValidationException) ErrorFault() smithy.ErrorFault

func (*ValidationException) ErrorMessage 

func (e *ValidationException) ErrorMessage() string

type Variable 

type Variable struct {

	// The ARN of the variable.
	Arn *string

	// The time when the variable was created.
	CreatedTime *string

	// The data source of the variable.
	DataSource DataSource

	// The data type of the variable. For more information see Variable types (https://docs.aws.amazon.com/frauddetector/latest/ug/create-a-variable.html#variable-types)
	// .
	DataType DataType

	// The default value of the variable.
	DefaultValue *string

	// The description of the variable.
	Description *string

	// The time when variable was last updated.
	LastUpdatedTime *string

	// The name of the variable.
	Name *string

	// The variable type of the variable. Valid Values: AUTH_CODE | AVS |
	// BILLING_ADDRESS_L1 | BILLING_ADDRESS_L2 | BILLING_CITY | BILLING_COUNTRY |
	// BILLING_NAME | BILLING_PHONE | BILLING_STATE | BILLING_ZIP | CARD_BIN |
	// CATEGORICAL | CURRENCY_CODE | EMAIL_ADDRESS | FINGERPRINT | FRAUD_LABEL |
	// FREE_FORM_TEXT | IP_ADDRESS | NUMERIC | ORDER_ID | PAYMENT_TYPE | PHONE_NUMBER |
	// PRICE | PRODUCT_CATEGORY | SHIPPING_ADDRESS_L1 | SHIPPING_ADDRESS_L2 |
	// SHIPPING_CITY | SHIPPING_COUNTRY | SHIPPING_NAME | SHIPPING_PHONE |
	// SHIPPING_STATE | SHIPPING_ZIP | USERAGENT
	VariableType *string
	// contains filtered or unexported fields
}

The variable.

type VariableEntry 

type VariableEntry struct {

	// The data source of the variable.
	DataSource *string

	// The data type of the variable.
	DataType *string

	// The default value of the variable.
	DefaultValue *string

	// The description of the variable.
	Description *string

	// The name of the variable.
	Name *string

	// The type of the variable. For more information see Variable types (https://docs.aws.amazon.com/frauddetector/latest/ug/create-a-variable.html#variable-types)
	// . Valid Values: AUTH_CODE | AVS | BILLING_ADDRESS_L1 | BILLING_ADDRESS_L2 |
	// BILLING_CITY | BILLING_COUNTRY | BILLING_NAME | BILLING_PHONE | BILLING_STATE |
	// BILLING_ZIP | CARD_BIN | CATEGORICAL | CURRENCY_CODE | EMAIL_ADDRESS |
	// FINGERPRINT | FRAUD_LABEL | FREE_FORM_TEXT | IP_ADDRESS | NUMERIC | ORDER_ID |
	// PAYMENT_TYPE | PHONE_NUMBER | PRICE | PRODUCT_CATEGORY | SHIPPING_ADDRESS_L1 |
	// SHIPPING_ADDRESS_L2 | SHIPPING_CITY | SHIPPING_COUNTRY | SHIPPING_NAME |
	// SHIPPING_PHONE | SHIPPING_STATE | SHIPPING_ZIP | USERAGENT
	VariableType *string
	// contains filtered or unexported fields
}

A variable in the list of variables for the batch create variable request.

type VariableImpactExplanation added in v1.17.0 

type VariableImpactExplanation struct {

	// The event variable name.
	EventVariableName *string

	// The raw, uninterpreted value represented as log-odds of the fraud. These values
	// are usually between -10 to +10, but range from - infinity to + infinity.
	//   - A positive value indicates that the variable drove the risk score up.
	//   - A negative value indicates that the variable drove the risk score down.
	LogOddsImpact *float32

	// The event variable's relative impact in terms of magnitude on the prediction
	// scores. The relative impact values consist of a numerical rating (0-5, 5 being
	// the highest) and direction (increased/decreased) impact of the fraud risk.
	RelativeImpact *string
	// contains filtered or unexported fields
}

The details of the event variable's impact on the prediction score.

type VariableImportanceMetrics added in v1.6.0 

type VariableImportanceMetrics struct {

	// List of variable metrics.
	LogOddsMetrics []LogOddsMetric
	// contains filtered or unexported fields
}

The variable importance metrics details.

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