Struct aws_sdk_frauddetector::operation::get_event_prediction::builders::GetEventPredictionFluentBuilder

pub struct GetEventPredictionFluentBuilder { /* private fields */ }

Fluent builder constructing a request to GetEventPrediction.

Evaluates an event against a detector version. If a version ID is not provided, the detector’s (ACTIVE) version is used.

Implementations

impl GetEventPredictionFluentBuilder

pub fn as_input(&self) -> &GetEventPredictionInputBuilder

Access the GetEventPrediction as a reference.

pub async fn send( self ) -> Result<GetEventPredictionOutput, SdkError<GetEventPredictionError, HttpResponse>>

Sends the request and returns the response.

If an error occurs, an SdkError will be returned with additional details that can be matched against.

By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.

pub fn customize( self ) -> CustomizableOperation<GetEventPredictionOutput, GetEventPredictionError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

pub fn detector_id(self, input: impl Into<String>) -> Self

The detector ID.

pub fn set_detector_id(self, input: Option<String>) -> Self

The detector ID.

pub fn get_detector_id(&self) -> &Option<String>

The detector ID.

pub fn detector_version_id(self, input: impl Into<String>) -> Self

The detector version ID.

pub fn set_detector_version_id(self, input: Option<String>) -> Self

The detector version ID.

pub fn get_detector_version_id(&self) -> &Option<String>

The detector version ID.

pub fn event_id(self, input: impl Into<String>) -> Self

The unique ID used to identify the event.

pub fn set_event_id(self, input: Option<String>) -> Self

The unique ID used to identify the event.

pub fn get_event_id(&self) -> &Option<String>

The unique ID used to identify the event.

pub fn event_type_name(self, input: impl Into<String>) -> Self

The event type associated with the detector specified for the prediction.

pub fn set_event_type_name(self, input: Option<String>) -> Self

The event type associated with the detector specified for the prediction.

pub fn get_event_type_name(&self) -> &Option<String>

The event type associated with the detector specified for the prediction.

pub fn entities(self, input: Entity) -> Self

Appends an item to entities.

To override the contents of this collection use set_entities.

The entity type (associated with the detector's event type) and specific entity ID representing who performed the event. If an entity id is not available, use "UNKNOWN."

pub fn set_entities(self, input: Option<Vec<Entity>>) -> Self

The entity type (associated with the detector's event type) and specific entity ID representing who performed the event. If an entity id is not available, use "UNKNOWN."

pub fn get_entities(&self) -> &Option<Vec<Entity>>

The entity type (associated with the detector's event type) and specific entity ID representing who performed the event. If an entity id is not available, use "UNKNOWN."

pub fn event_timestamp(self, input: impl Into<String>) -> Self

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

pub fn set_event_timestamp(self, input: Option<String>) -> Self

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

pub fn get_event_timestamp(&self) -> &Option<String>

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

pub fn event_variables(self, k: impl Into<String>, v: impl Into<String>) -> Self

Adds a key-value pair to eventVariables.

To override the contents of this collection use set_event_variables.

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.

You must provide at least one eventVariable

To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:

For Amazon Fraud Detector trained models:

If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.

For imported SageMaker models:

If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.

pub fn set_event_variables(self, input: Option<HashMap<String, String>>) -> Self

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.

You must provide at least one eventVariable

To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:

For Amazon Fraud Detector trained models:

If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.

For imported SageMaker models:

If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.

pub fn get_event_variables(&self) -> &Option<HashMap<String, 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.

You must provide at least one eventVariable

To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:

For Amazon Fraud Detector trained models:

If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.

For imported SageMaker models:

If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.

pub fn external_model_endpoint_data_blobs( self, k: impl Into<String>, v: ModelEndpointDataBlob ) -> Self

Adds a key-value pair to externalModelEndpointDataBlobs.

To override the contents of this collection use set_external_model_endpoint_data_blobs.

The Amazon SageMaker model endpoint input data blobs.

pub fn set_external_model_endpoint_data_blobs( self, input: Option<HashMap<String, ModelEndpointDataBlob>> ) -> Self

The Amazon SageMaker model endpoint input data blobs.

pub fn get_external_model_endpoint_data_blobs( &self ) -> &Option<HashMap<String, ModelEndpointDataBlob>>

The Amazon SageMaker model endpoint input data blobs.

Trait Implementations

impl Clone for GetEventPredictionFluentBuilder

fn clone(&self) -> GetEventPredictionFluentBuilder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for GetEventPredictionFluentBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.