In the context of developing a random forest model for fraud detection at a bank, the dataset comprises transactions with only 1% identified as fraudulent. The bank is concerned about the high cost of false negatives and requires a solution that not only improves the model's ability to detect fraudulent transactions but also adheres to strict compliance regulations. Which of the following data transformation strategies would most effectively enhance the classifier's performance under these constraints? (Choose two options)