Creating CSV file - Amazon Fraud Detector

Creating CSV file

Amazon Fraud Detector requires that the first row of your CSV file contain column headers. The column headers in your CSV file must map to the variables that are defined in the event type. For an example dataset, see Get and upload example training data

The Online Fraud Insights model requires a training dataset that has at least 2 variables and up to 100 variables. In addition to the event variables, the training dataset must contain the following headers:

  • EVENT_TIMESTAMP - Defines when the event occurred

  • EVENT_LABEL - Classifies the event as fraudulent or legitimate. The values in the column must correspond to the values defined in the event type.

For example, the following sample CSV data maps to the event type shown in Create event dataset Create event types. This data represents historical registration events from an online merchant:

EVENT_TIMESTAMP,EVENT_LABEL,ip_address,email_address 4/10/2019 11:05,fraud,209.146.137.48,fake_burtonlinda@example.net 12/20/2018 20:04,legit,203.0.112.189,fake_davidbutler@example.org 3/14/2019 10:56,legit,169.255.33.54,fake_shelby76@example.net 1/3/2019 8:38,legit,192.119.44.26,fake_curtis40@example.com 9/25/2019 3:12,legit,192.169.85.29,fake_rmiranda@example.org

A simplified version of the corresponding event type is represented below. The event variables correspond to the headers in the CSV file and the values in EVENT_LABEL correspond to the values in the labels list.

( name = 'sample_registration', eventVariables = ['ip_address', 'email_address'], labels = ['legit', 'fraud'], entityTypes = ['sample_customer'] )