[ aws . frauddetector ]
describe-model-versions¶
Description¶
Gets all of the model versions for the specified model type or for the specified model type and model ID. You can also get details for a single, specified model version.
See also: AWS API Documentation
See ‘aws help’ for descriptions of global parameters.
Synopsis¶
describe-model-versions
[--model-id <value>]
[--model-version-number <value>]
[--model-type <value>]
[--next-token <value>]
[--max-results <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
Options¶
--model-id (string)
The model ID.
--model-version-number (string)
The model version number.
--model-type (string)
The model type.
Possible values:
ONLINE_FRAUD_INSIGHTS
TRANSACTION_FRAUD_INSIGHTS
--next-token (string)
The next token from the previous results.
--max-results (integer)
The maximum number of results to return.
--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¶
modelVersionDetails -> (list)
The model version details.
(structure)
The details of the model version.
modelId -> (string)
The model ID.
modelType -> (string)
The model type.
modelVersionNumber -> (string)
The model version number.
status -> (string)
The status of the model version.
trainingDataSource -> (string)
The model version 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 external events data details. This will be populated if the
trainingDataSourcefor the model version is specified asEXTERNAL_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 ingested events data details. This will be populated if the
trainingDataSourcefor the model version is specified asINGESTED_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.
trainingResult -> (structure)
The training results.
dataValidationMetrics -> (structure)
The validation metrics.
fileLevelMessages -> (list)
The file-specific model training validation messages.
(structure)
The message details.
title -> (string)
The message title.
content -> (string)
The message content.
type -> (string)
The message type.
fieldLevelMessages -> (list)
The field-specific model training validation messages.
(structure)
The message details.
fieldName -> (string)
The field name.
identifier -> (string)
The message ID.
title -> (string)
The message title.
content -> (string)
The message content.
type -> (string)
The message type.
trainingMetrics -> (structure)
The training metric details.
auc -> (float)
The area under the curve. This summarizes true positive rate (TPR) and false positive rate (FPR) across all possible model score thresholds. A model with no predictive power has an AUC of 0.5, whereas a perfect model has a score of 1.0.
metricDataPoints -> (list)
The data points details.
(structure)
Model performance metrics data points.
fpr -> (float)
The false positive rate. This is the percentage of total legitimate events that are incorrectly predicted as fraud.
precision -> (float)
The percentage of fraud events correctly predicted as fraudulent as compared to all events predicted as fraudulent.
tpr -> (float)
The true positive rate. This is the percentage of total fraud the model detects. Also known as capture rate.
threshold -> (float)
The model threshold that specifies an acceptable fraud capture rate. For example, a threshold of 500 means any model score 500 or above is labeled as fraud.
variableImportanceMetrics -> (structure)
The variable importance metrics.
logOddsMetrics -> (list)
List of variable metrics.
(structure)
The log odds metric details.
variableName -> (string)
The name of the variable.
variableType -> (string)
The type of variable.
variableImportance -> (float)
The relative importance of the variable. For more information, see Model variable importance .
lastUpdatedTime -> (string)
The timestamp when the model was last updated.
createdTime -> (string)
The timestamp when the model was created.
arn -> (string)
The model version ARN.
nextToken -> (string)
The next token.