[ aws . frauddetector ]

get-model-version

Description

Gets the details of the specified model version.

See also: AWS API Documentation

See ‘aws help’ for descriptions of global parameters.

Synopsis

  get-model-version
--model-id <value>
--model-type <value>
--model-version-number <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options

--model-id (string)

The model ID.

--model-type (string)

The model type.

Possible values:

  • ONLINE_FRAUD_INSIGHTS

  • TRANSACTION_FRAUD_INSIGHTS

--model-version-number (string)

The model version number.

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See ‘aws help’ for descriptions of global parameters.

Output

modelId -> (string)

The model ID.

modelType -> (string)

The model type.

modelVersionNumber -> (string)

The model version number.

trainingDataSource -> (string)

The training data source.

trainingDataSchema -> (structure)

The training data schema.

modelVariables -> (list)

The training data schema variables.

(string)

labelSchema -> (structure)

The label schema.

labelMapper -> (map)

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.

key -> (string)

value -> (list)

(string)

unlabeledEventsTreatment -> (string)

The action to take for unlabeled events.

externalEventsDetail -> (structure)

The details of the external events data used for training the model version. This will be populated if the trainingDataSource is EXTERNAL_EVENTS

dataLocation -> (string)

The Amazon S3 bucket location for the data.

dataAccessRoleArn -> (string)

The ARN of the role that provides Amazon Fraud Detector access to the data location.

ingestedEventsDetail -> (structure)

The details of the ingested events data used for training the model version. This will be populated if the trainingDataSource is INGESTED_EVENTS .

ingestedEventsTimeWindow -> (structure)

The start and stop time of the ingested events.

startTime -> (string)

Timestamp of the first ingensted event.

endTime -> (string)

Timestamp of the final ingested event.

status -> (string)

The model version status.

Possible values are:

  • TRAINING_IN_PROGRESS

  • TRAINING_COMPLETE

  • ACTIVATE_REQUESTED

  • ACTIVATE_IN_PROGRESS

  • ACTIVE

  • INACTIVATE_REQUESTED

  • INACTIVATE_IN_PROGRESS

  • INACTIVE

  • ERROR

arn -> (string)

The model version ARN.