AWS frauddetector documentation change
Summary
Fixed URL formatting in multiple documentation links by adding an extra slash after domain
Security assessment
The changes are purely URL syntax corrections for existing fraud detection documentation links. No modifications to security guidance or data validation requirements were made.
Diff
diff --git a/frauddetector/latest/ug/online-fraud-insights.md b/frauddetector/latest/ug/online-fraud-insights.md index 31187d53d..d61f7618c 100644 --- a//frauddetector/latest/ug/online-fraud-insights.md +++ b//frauddetector/latest/ug/online-fraud-insights.md @@ -29 +29 @@ Your dataset must contain the column header EVENT_LABEL. This variable classifie -See [Gather event data](https://docs.aws.amazon.com/frauddetector/latest/ug/create-event-dataset.html#gather-event-data) for information on selecting data for training your Online Fraud Insights model. +See [Gather event data](https://docs.aws.amazon.com//frauddetector/latest/ug/create-event-dataset.html#gather-event-data) for information on selecting data for training your Online Fraud Insights model. @@ -35 +35 @@ The Online Fraud Insights training process samples and partitions historic data -The Online Fraud Insights model requires at least two variables, apart from the required event metadata, that has passed [data validation](https://docs.aws.amazon.com/frauddetector/latest/ug/create-event-dataset.html#dataset-validation) for model training and allows up to 100 variables per model. Generally, the more variables you provide, the better the model can differentiate between fraud and legitimate events. While the Online Fraud Insights model can support dozens of variables, including custom variables, we recommend including IP address and email address because these variables are typically most effective at identifying the entity being evaluated. +The Online Fraud Insights model requires at least two variables, apart from the required event metadata, that has passed [data validation](https://docs.aws.amazon.com//frauddetector/latest/ug/create-event-dataset.html#dataset-validation) for model training and allows up to 100 variables per model. Generally, the more variables you provide, the better the model can differentiate between fraud and legitimate events. While the Online Fraud Insights model can support dozens of variables, including custom variables, we recommend including IP address and email address because these variables are typically most effective at identifying the entity being evaluated. @@ -39 +39 @@ The Online Fraud Insights model requires at least two variables, apart from the -As part of the training process, Online Fraud Insights will validate the dataset for data quality issues that may impact model training. After validating the data, Amazon Fraud Detector will take appropriate action to build the best possible model. This includes issuing warnings for potential data quality issues, automatically removing variables that have data quality issues, or issuing an error and stopping the model training process. For more information, see [dataset validation](https://docs.aws.amazon.com/frauddetector/latest/ug/create-event-dataset.html#dataset-validation). +As part of the training process, Online Fraud Insights will validate the dataset for data quality issues that may impact model training. After validating the data, Amazon Fraud Detector will take appropriate action to build the best possible model. This includes issuing warnings for potential data quality issues, automatically removing variables that have data quality issues, or issuing an error and stopping the model training process. For more information, see [dataset validation](https://docs.aws.amazon.com//frauddetector/latest/ug/create-event-dataset.html#dataset-validation).