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AWS for Query.Farm

aws.frauddetector.get_model_version

Example SQL Queries

SELECT * FROM
aws.frauddetector.get_model_version
WHERE
"model_id" = 'VALUE'
AND "model_type" = 'VALUE'
AND "model_version_number" = 'VALUE';

Description

Gets the details of the specified model version.

Table Definition

Column NameColumn Data Type
model_id Required Input Column

The model ID.

VARCHAR
model_type Required Input Column

The model type.

VARCHAR
model_version_number Required Input Column

The model version number.

VARCHAR
_aws_profile Input Column

The AWS profile defines the AWS identity used. It can be defined via credentials or by assuming a IAM role.

STRUCT(
    "type" VARCHAR,
    "name" VARCHAR,
    "account_id" VARCHAR,
    "via_profile_name" VARCHAR,
    "assumed_role_arn" VARCHAR,
    "organization" STRUCT(
        "account_name" VARCHAR,
        "id" VARCHAR,
        "tags" STRUCT(
            "key" VARCHAR,
            "value" VARCHAR
        )[],
        "master_account" STRUCT(
            "id" VARCHAR,
            "email" VARCHAR
        ),
        "parents" STRUCT(
            "type" VARCHAR,
            "id" VARCHAR,
            "name" VARCHAR,
            "tags" STRUCT(
                "key" VARCHAR,
                "value" VARCHAR
            )[]
        )[]
    )
)
Show child fields
_aws_profile.account_id

The AWS account id

_aws_profile.assumed_role_arn

The ARN of the assumed role

_aws_profile.name

The unique name of the profile.

_aws_profile.organization

Information about this profile's membership in the AWS organization.

Show child fields
_aws_profile.organization.account_name

The name of account speciifed by the organization

_aws_profile.organization.id

The organization id

_aws_profile.organization.master_account
Show child fields
_aws_profile.organization.master_account.email

The organization master account email address

_aws_profile.organization.master_account.id

The organization master account id

_aws_profile.organization.parents[]
Show child fields
_aws_profile.organization.parents[].id

The id of the parent

_aws_profile.organization.parents[].name

The name of the parent

_aws_profile.organization.parents[].tags[]
Show child fields
_aws_profile.organization.parents[].tags[].key
_aws_profile.organization.parents[].tags[].value
_aws_profile.organization.parents[].type

The type of parent can be an organization unit or a root

_aws_profile.organization.tags[]
Show child fields
_aws_profile.organization.tags[].key
_aws_profile.organization.tags[].value
_aws_profile.type

The type of profile, either 'credentials' or 'assumed_role'

_aws_profile.via_profile_name

This IAM role for this profile is assumed by first utilizing another profile with this name to obtain credentials.

_aws_region Input Column

The AWS region to use.

VARCHAR
arn

The model version ARN.

VARCHAR
external_events_detail

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

STRUCT(
    "data_location" VARCHAR,
    "data_access_role_arn" VARCHAR
)
Show child fields
external_events_detail.data_access_role_arn

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

external_events_detail.data_location

The Amazon S3 bucket location for the data.

ingested_events_detail

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

STRUCT(
    "ingested_events_time_window" STRUCT(
        "start_time" VARCHAR,
        "end_time" VARCHAR
    )
)
Show child fields
ingested_events_detail.ingested_events_time_window

The start and stop time of the ingested events.

Show child fields
ingested_events_detail.ingested_events_time_window.end_time

Timestamp of the final ingested event.

ingested_events_detail.ingested_events_time_window.start_time

Timestamp of the first ingensted event.

status

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 

VARCHAR
training_data_schema

The training data schema.

STRUCT(
    "model_variables" VARCHAR[],
    "label_schema" STRUCT(
        "label_mapper" MAP(VARCHAR, VARCHAR[]),
        "unlabeled_events_treatment" VARCHAR
    )
)
Show child fields
training_data_schema.label_schema

The label schema.

Show child fields
training_data_schema.label_schema.label_mapper

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.

training_data_schema.label_schema.unlabeled_events_treatment

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.

training_data_schema.model_variables[]
training_data_source

The training data source.

VARCHAR