The correct answer is C. Binary.
Bernoulli Naive Bayes is a classification algorithm that uses Bayes’ theorem to classify data. It assumes that the features are independent of each other, and that the target variable is binary. This means that the algorithm can only classify data into two categories.
A continuous distribution is a probability distribution that can take on any value within a given range. A discrete distribution is a probability distribution that can only take on a finite number of values. A binary distribution is a special type of discrete distribution that can only take on two values, 0 and 1.
Bernoulli Naive Bayes is a binary classifier because it can only classify data into two categories. The two categories are usually labeled as “positive” and “negative”. For example, a Bernoulli Naive Bayes classifier could be used to classify email messages as spam or not spam.
Bernoulli Naive Bayes is a simple and effective classification algorithm. It is often used in spam filtering, text classification, and other applications where the target variable is binary.