class Aws::FraudDetector::Types::GetEventPredictionRequest

@note When making an API call, you may pass GetEventPredictionRequest

data as a hash:

    {
      detector_id: "string", # required
      detector_version_id: "wholeNumberVersionString",
      event_id: "string", # required
      event_type_name: "string", # required
      entities: [ # required
        {
          entity_type: "string", # required
          entity_id: "identifier", # required
        },
      ],
      event_timestamp: "utcTimestampISO8601", # required
      event_variables: { # required
        "variableName" => "variableValue",
      },
      external_model_endpoint_data_blobs: {
        "string" => {
          byte_buffer: "data",
          content_type: "contentType",
        },
      },
    }

@!attribute [rw] detector_id

The detector ID.
@return [String]

@!attribute [rw] detector_version_id

The detector version ID.
@return [String]

@!attribute [rw] event_id

The unique ID used to identify the event.
@return [String]

@!attribute [rw] event_type_name

The event type associated with the detector specified for the
prediction.
@return [String]

@!attribute [rw] 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."
@return [Array<Types::Entity>]

@!attribute [rw] event_timestamp

Timestamp that defines when the event under evaluation occurred.
@return [String]

@!attribute [rw] 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

* If detectorVersion is associated with a modelVersion, you must
  provide at least one associated eventVariable

To ensure highest possible 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 External models ( for example, imported SageMaker):**

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.
@return [Hash<String,String>]

@!attribute [rw] external_model_endpoint_data_blobs

The Amazon SageMaker model endpoint input data blobs.
@return [Hash<String,Types::ModelEndpointDataBlob>]

@see docs.aws.amazon.com/goto/WebAPI/frauddetector-2019-11-15/GetEventPredictionRequest AWS API Documentation

Constants

SENSITIVE