The rule execution mode for the rules included in the detector version.

You can define and edit the rule mode at the detector version level, when it is in draft status.

If you specify FIRST_MATCHED, Amazon Fraud Detector evaluates rules sequentially, first to last, stopping at the first matched rule. Amazon Fraud dectector then provides the outcomes for that single rule.

If you specifiy ALL_MATCHED, Amazon Fraud Detector evaluates all rules and returns the outcomes for all matched rules.

The default behavior is FIRST_MATCHED.

The model versions to include in the detector version.

The Amazon Sagemaker model endpoints to include in the detector version.

The description of the detector version.

A collection of key and value pairs.

The ID of the detector under which you want to create a new version.

The rules to include in the detector version.

The status of the detector version.

The ID for the created detector.

The ID for the created version's parent detector.

The response's http status code.

The list of variable names to get.

The returned variables.

The errors from the request.

The response's http status code.

The details of the external events data used for training the model version. Required if trainingDataSource is EXTERNAL_EVENTS.

The details of the ingested event used for training the model version. Required if your trainingDataSource is INGESTED_EVENTS.

A collection of key and value pairs.

The model ID.

The model type.

The major version number.

The status of the updated model version.

The model type.

The model ID.

The model version number of the model version updated.

The response's http status code.

The model ID of the model version to delete.

The model type of the model version to delete.

The model version number of the model version to delete.

The response's http status code.

The detector ID.

The detector version ID.

The description.

The response's http status code.

The ID of the batch import job to delete.

The response's http status code.

Undocumented member.

The response's http status code.

The label description.

The label name.

The response's http status code.

The Amazon SageMaker model endpoint.

The next page token for the request.

The maximum number of objects to return for the request.

The next page token to be used in subsequent requests.

Gets the Amazon SageMaker models.

The response's http status code.

The next token for the subsequent request.

The detector ID.

The maximum number of objects to return for the request.

The next page token.

The detectors.

The response's http status code.

The name of the label to delete.

The response's http status code.

The name of the variable to delete.

The response's http status code.

The new default value of the variable.

The variable type. For more information see Variable types.

The new description.

The name of the variable.

The response's http status code.

The variable type. 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

The description.

A collection of key and value pairs.

The name of the variable.

The data type.

The source of the data.

The default value for the variable when no value is received.

The response's http status code.

A collection of key-value pairs associated with this request.

The ID of the batch import job. The ID cannot be of a past job, unless the job exists in CREATE_FAILED state.

The URI that points to the Amazon S3 location of your data file.

The URI that points to the Amazon S3 location for storing your results.

The name of the event type.

The ARN of the IAM role created for Amazon S3 bucket that holds your data file. The IAM role must have read and write permissions to both input and output S3 buckets.

The response's http status code.

The rule description.

A collection of key and value pairs.

The rule ID.

The detector ID for the rule's parent detector.

The rule expression.

The language of the rule.

The outcome or outcomes returned when the rule expression matches.

The created rule.

The response's http status code.

The next token from the previous results.

The maximum number of objects to return for the request.

The ARN that specifies the resource whose tags you want to list.

The next token for subsequent requests.

A collection of key and value pairs.

The response's http status code.

The model type.

The model ID.

The next token for the subsequent request.

The maximum number of objects to return for the request.

The array of models.

The next page token to be used in subsequent requests.

The response's http status code.

The description.

The tags to assign to the rule version.

The rule to update.

The rule expression.

The language.

The outcomes.

The new rule version that was created.

The response's http status code.

Specifies whether or not to delete any predictions associated with the event.

The ID of the event to delete.

The name of the event type.

The response's http status code.

The ID of the batch prediction job to cancel.

The response's http status code.

The model ID of the model version to update.

The model type.

The model version number.

The model version status.

The response's http status code.

The batch prediction job for which to get the details.

The next token from the previous request.

The maximum number of objects to return for the request.

An array containing the details of each batch prediction job.

The next token for the subsequent request.

The response's http status code.

The model description.

A collection of key and value pairs.

The model ID.

The model type.

The name of the event type.

The response's http status code.

The next token for the subsequent request.

The name of the label or labels to get.

The maximum number of objects to return for the request.

The next page token.

An array of labels.

The response's http status code.

The model ID.

The model type.

The model version number.

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

The model type.

The model ID.

The model version ARN.

The training data source.

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

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

The model version number.

The training data schema.

The response's http status code.

A collection of key and value pairs.

The model endpoints name.

The source of the model.

The IAM role used to invoke the model endpoint.

The model endpoint input configuration.

The model endpoint output configuration.

The model endpoint’s status in Amazon Fraud Detector.

The response's http status code.

The endpoint of the Amazon Sagemaker model to delete.

The response's http status code.

The next token for the subsequent request.

The name.

The maximum number of objects to return for the request.

An array of entity types.

The next page token.

The response's http status code.

The model ID of the model to delete.

The model type of the model to delete.

The response's http status code.

The new model description.

The model ID.

The model type.

The response's http status code.

Details of the external events data used for model version training. Required if trainingDataSource is EXTERNAL_EVENTS.

Details of the ingested events data used for model version training. Required if trainingDataSource is INGESTED_EVENTS.

A collection of key and value pairs.

The model ID.

The model type.

The training data source location in Amazon S3.

The training data schema.

The model version status.

The model type.

The model ID.

The model version number of the model version created.

The response's http status code.

The name of the event type.

Name of event type for which to delete the events.

The status of the delete request.

The response's http status code.

The KMS encryption key ARN.

The response's http status code.

The next token from the previous response.

The maximum number of results to return for the request.

The detector ID.

The status and description for each detector version.

The detector ARN.

The next token to be used for subsequent requests.

The detector ID.

The response's http status code.

The next page token for the request.

The name of the outcome or outcomes to get.

The maximum number of objects to return for the request.

The outcomes.

The next page token for subsequent requests.

The response's http status code.

The detector version ID.

The Amazon SageMaker model endpoint input data blobs.

The detector ID.

The unique ID used to identify the event.

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

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."

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

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.

The model scores. Amazon Fraud Detector generates model scores between 0 and 1000, where 0 is low fraud risk and 1000 is high fraud risk. Model scores are directly related to the false positive rate (FPR). For example, a score of 600 corresponds to an estimated 10% false positive rate whereas a score of 900 corresponds to an estimated 2% false positive rate.

The model scores for Amazon SageMaker models.

The results from the rules.

The response's http status code.

The ID of the batch prediction job to delete.

The response's http status code.

The ID of the event to retrieve.

The event type of the event to retrieve.

The details of the event.

The response's http status code.

The rule to update.

The rule description.

The response's http status code.

The description.

A collection of key and value pairs.

The name of the entity type.

The response's http status code.

The detector version.

A collection of key and value pairs.

The ID of the batch prediction job.

The Amazon S3 location of your training file.

The Amazon S3 location of your output file.

The name of the event type.

The name of the detector.

The ARN of the IAM role to use for this job request.

The response's http status code.

The name of the entity type to delete.

The response's http status code.

The name of the event type to delete.

The response's http status code.

The event type labels.

Specifies if ingenstion is enabled or disabled.

The description of the event type.

A collection of key and value pairs.

The name.

The event type variables.

The entity type for the event type. Example entity types: customer, merchant, account.

The response's http status code.

The detector ID.

The detector version ID.

The new status.

The response's http status code.

The ID of an in-progress batch import job to cancel.

Amazon Fraud Detector will throw an error if the batch import job is in FAILED, CANCELED, or COMPLETED state.

The response's http status code.

The timestamp associated with the label. Required if specifying assignedLabel.

The label to associate with the event. Required if specifying labelTimestamp.

The event ID to upload.

The event type name of the event.

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

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.

An array of entities.

The response's http status code.

The resource ARN.

The tags to assign to the resource.

The response's http status code.

The KMS encryption key.

The response's http status code.

The ID of the event associated with the label to update.

The event type of the event associated with the label to update.

The new label to assign to the event.

The timestamp associated with the label. The timestamp must be specified using ISO 8601 standard in UTC.

The response's http status code.

The ID of the batch import job to get.

The next token from the previous request.

The maximum number of objects to return for request.

The next token for the subsequent resquest.

An array containing the details of each batch import job.

The response's http status code.

Name of event type for which to get the deletion status.

The event type name.

The deletion status.

The response's http status code.

The name of the outcome to delete.

The response's http status code.

The rule version.

The rule ID.

The next page token.

The maximum number of rules to return for the request.

The detector ID.

The details of the requested rule.

The next page token to be used in subsequent requests.

The response's http status code.

The next page token of the get variable request.

The name of the variable.

The max size per page determined for the get variable request.

The names of the variables returned.

The next page token to be used in subsequent requests.

The response's http status code.

The ARN of the resource from which to remove the tag.

The resource ARN.

The response's http status code.

The description of the detector.

A collection of key and value pairs.

The detector ID.

The name of the event type.

The response's http status code.

The outcome description.

A collection of key and value pairs.

The name of the outcome.

The response's http status code.

The ID of the detector to delete.

The response's http status code.

The model type.

The model ID.

The next token from the previous results.

The model version number.

The maximum number of results to return.

The next token.

The model version details.

The response's http status code.

A collection of key and value pairs.

The list of variables for the batch create variable request.

Provides the errors for the BatchCreateVariable request.

The response's http status code.

The detector ID.

The detector version ID.

The status of the detector version.

The execution mode of the rule in the dectector

FIRST_MATCHED indicates that Amazon Fraud Detector evaluates rules sequentially, first to last, stopping at the first matched rule. Amazon Fraud dectector then provides the outcomes for that single rule.

ALL_MATCHED indicates that Amazon Fraud Detector evaluates all rules and returns the outcomes for all matched rules. You can define and edit the rule mode at the detector version level, when it is in draft status.

The timestamp when the detector version was last updated.

The detector version ARN.

The rules included in the detector version.

The detector version ID.

The timestamp when the detector version was created.

The model versions included in the detector version.

The detector ID.

The Amazon SageMaker model endpoints included in the detector version.

The detector version description.

The response's http status code.

The next token for the subsequent request.

The name.

The maximum number of objects to return for the request.

An array of event types.

The next page token.

The response's http status code.

The ID of the parent detector for the detector version to delete.

The ID of the detector version to delete.

The response's http status code.

The rule execution mode to add to the detector.

If you specify FIRST_MATCHED, Amazon Fraud Detector evaluates rules sequentially, first to last, stopping at the first matched rule. Amazon Fraud dectector then provides the outcomes for that single rule.

If you specifiy ALL_MATCHED, Amazon Fraud Detector evaluates all rules and returns the outcomes for all matched rules. You can define and edit the rule mode at the detector version level, when it is in draft status.

The default behavior is FIRST_MATCHED.

The model versions to include in the detector version.

The detector version description.

The parent detector ID for the detector version you want to update.

The detector version ID.

The Amazon SageMaker model endpoints to include in the detector version.

The rules to include in the detector version.

The response's http status code.

The name.

The error code.

The error message.

The error name.

The error code.

The error message.

The reason batch import job failed.

The ARN of the IAM role to use for this job request.

The status of the batch import job.

The number of records processed by batch import job.

The total number of records in the batch import job.

The ID of the batch import job.

The ARN of the batch import job.

Timestamp of when the batch import job started.

The name of the event type.

Timestamp of when batch import job completed.

The Amazon S3 location of your output file.

The Amazon S3 location of your data file for batch import.

The number of records that failed to import.

The reason a batch prediction job failed.

The ARN of the IAM role to use for this job request.

The batch prediction status.

The number of records processed by the batch prediction job.

The total number of records in the batch prediction job.

Timestamp of most recent heartbeat indicating the batch prediction job was making progress.

The job ID for the batch prediction.

The ARN of batch prediction job.

Timestamp of when the batch prediction job started.

The name of the event type.

Timestamp of when the batch prediction job completed.

The Amazon S3 location of your output file.

The name of the detector.

The detector version.

The Amazon S3 location of your training file.

The field-specific model training validation messages.

The file-specific model training validation messages.

Timestamp of when the detector was last updated.

The detector ARN.

Timestamp of when the detector was created.

The name of the event type.

The detector ID.

The detector description.

The detector version status.

Timestamp of when the detector version was last updated.

The detector version ID.

The detector version description.

The entity type.

The entity ID. If you do not know the entityId, you can pass unknown, which is areserved string literal.

Timestamp of when the entity type was last updated.

The entity type ARN.

Timestamp of when the entity type was created.

The entity type name.

The entity type description.

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

The event entities.