You are developing an ML model using a dataset with categorical input variables. You have randomly split half of the data into training and test sets. After applying one-hot encoding on the categorical variables in the training set, you discover that one categorical variable is missing from the test set. What should you do?

A. Use sparse representation in the test set. B. Randomly redistribute the data, with 70% for the training set and 30% for the test set C. Apply one-hot encoding on the categorical variables in the test data D. Collect more data representing all categories