Amazon Fraud Detector introduces Cold Start model training for customers with limited historical data
Today, Amazon Fraud Detector (AFD) announced the launch of the Cold Start feature. Now customers can start training a sign-up or a transaction frauds detection model with minimal historical-data. Up to now, AFD customers were required to provide 10K+ labeled events with at least 400 examples of fraud to train a model. With the release of Cold Start only 50 labeled fraud events and 50 unlabeled events are necessary. The new feature introduces intelligent methods for treating your unlabeled data and optimizes model training with small datasets.