A financial institution is developing a machine learning model to detect fraudulent transactions. The team has a large dataset of transactions, but only a small portion of them are labeled as fraudulent or legitimate. To make the best use of both labeled and unlabeled data, they are considering semi-supervised learning. Which of the following are examples of semi-supervised learning? (Select TWO.)