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
}

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
}

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
}

type AccessDeniedException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

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
}

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
}

type AggregatedVariablesImportanceMetrics struct {

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

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
}

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"
)

type BatchCreateVariableError struct {

	// The error code.
	Code int32

	// The error message.
	Message *string

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

type BatchGetVariableError struct {

	// The error code.
	Code int32

	// The error message.
	Message *string

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

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
}

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
}

type ConflictException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

type DataSource string

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

type DataType string

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

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
}

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
}

type DetectorVersionStatus string

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

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
}

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
}

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
}

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
}

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
}

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
}

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
}

type EventIngestion string

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

type EventOrchestration struct {

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

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
}

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
}

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
}

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
}

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
}

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
}

type ExternalModelSummary struct {

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

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

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
}

type FileValidationMessage struct {

	// The message content.
	Content *string

	// The message title.
	Title *string

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

type FilterCondition struct {

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

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
}

type IngestedEventsDetail struct {

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

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
}

type InternalServerException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

type KMSKey struct {

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

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
}

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
}

type Language string

const (
	LanguageDetectorpl Language = "DETECTORPL"
)

type ListUpdateMode string

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

type LogOddsMetric struct {

	// The relative importance of the variable. For more information, see [Model variable importance].
	//
	// [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
}

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
}

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
}

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
}

type ModelEndpointStatus string

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

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
}

type ModelInputDataFormat string

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

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
}

type ModelOutputDataFormat string

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

type ModelScores struct {

	// The model version.
	ModelVersion *ModelVersion

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

type ModelSource string

const (
	ModelSourceSagemaker ModelSource = "SAGEMAKER"
)

type ModelTypeEnum string

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

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
}

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
}

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
}

type ModelVersionStatus string

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

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
}

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
}

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
}

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
}

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
}

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
}

type ResourceNotFoundException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

type ResourceUnavailableException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

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
}

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
}

type RuleExecutionMode string

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

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
}

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
}

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
}

type TFITrainingMetricsValue struct {

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

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

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
}

type ThrottlingException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

type TrainingDataSchema struct {

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

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

type TrainingDataSourceEnum string

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

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
}

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
}

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
}

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
}

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
}

type UnlabeledEventsTreatment string

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

type ValidationException struct {
	Message *string

	ErrorCodeOverride *string
	// contains filtered or unexported fields
}

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].
	//
	// [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
}

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].
	//
	// 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
	//
	// [Variable types]: https://docs.aws.amazon.com/frauddetector/latest/ug/create-a-variable.html#variable-types
	VariableType *string
	// contains filtered or unexported fields
}

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
}

type VariableImportanceMetrics struct {

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