The log odds metric details.

The details of the impact of aggregated variables on the prediction score.

The details of the relative importance of the aggregated variables.

The metadata of a list.

The Account Takeover Insights (ATI) model performance metrics data points.

The Account Takeover Insights (ATI) model performance score.

The Account Takeover Insights (ATI) model training metric details.

Provides the error of the batch create variable API.

Provides the error of the batch get variable API.

The batch import job details.

The batch prediction details.

The model training data validation metrics.

The detector.

The summary of the detector version.

The entity details.

The entity type details.

The details of the external (Amazon Sagemaker) model evaluated for generating predictions.

The model version evaluated for generating prediction.

The details of the rule used for evaluating variable values.

The event details.

Information about the summary of an event prediction.

The event type details.

Information about the summary of an event variable that was evaluated for generating prediction.

Details for the external events data used for model version training.

The Amazon SageMaker model.

The fraud prediction scores from Amazon SageMaker model.

The Amazon SageMaker model.

The message details.

The message details.

A conditional statement for filtering a list of past predictions.

The details of the ingested event.

Data about the stored events.

The start and stop time of the ingested events.

The KMS key details.

The label details.

The label schema.

The log odds metric details.

Model performance metrics data points.

The model.

A pre-formed Amazon SageMaker model input you can include if your detector version includes an imported Amazon SageMaker model endpoint with pass-through input configuration.

The Amazon SageMaker model input configuration.

Provides the Amazon Sagemaker model output configuration.

The fraud prediction scores.

The model version.

The details of the model version.

The model version evalutions.

The Online Fraud Insights (OFI) model performance metrics data points.

The Online Fraud Insights (OFI) model performance score.

The Online Fraud Insights (OFI) model training metric details.

The outcome.

The prediction explanations that provide insight into how each event variable impacted the model version's fraud prediction score.

The time period for when the predictions were generated.

A rule.

The details of the rule.

The rule results.

A key and value pair.

The performance metrics data points for Transaction Fraud Insights (TFI) model.

The Transaction Fraud Insights (TFI) model performance score.

The Transaction Fraud Insights (TFI) model training metric details.

The training data schema.

The training metric details.

The training metrics details.

The training result details.

The training result details.

Range of area under curve (auc) expected from the model. A range greater than 0.1 indicates higher model uncertainity. A range is the difference between upper and lower bound of auc.

The variable.

A variable in the list of variables for the batch create variable request.

The details of the event variable's impact on the prediction score.

The variable importance metrics details.