You work for a bank and are building a random forest model for fraud detection. You have a dataset that includes transactions, of which 1% are identified as fraudulent. Which data transformation strategy would likely improve the performance of your classifier?

A. Write your data in TFRecords. B. Z-normalize all the numeric features. C. Oversample the fraudulent transaction 10 times. D. Use one-hot encoding on all categorical features.