Consider the task of classifying first-names as masculine vs. feminine. Explain why a Naive Bayes model that considers features (suffix[-1], suffix[-2]) (that is, 2 features for the last 2 letters in the word) behaves differently from one that considers a single feature (suffix[-12]) - that is, a single feature containing the last 2 letters.