Which of the following are true or false. Briefly justify your answer.

a. In the case of a binary class and all binary features, Naive Bayes is a linear classifier. 

b. Naive Bayes trained using maximum-likelihood parameter estimation is guaranteed not to perform worse if more features are added. 

c. Naive Bayes trained using maximum-likelihood parameter estimation generally performs better on the training set if add-k smoothing is use.