The correct answer is A. Continuous.
Gaussian Naive Bayes is a type of supervised machine learning algorithm that uses Bayes’ theorem to classify data. It is a probabilistic classifier, which means that it assigns a probability to each class label for each data point. The probability of a data point belonging to a class is calculated based on the class’s prior probability and the likelihood of the data point given the class.
Gaussian Naive Bayes is a simple and efficient algorithm that is often used for text classification and spam filtering. It is also used in other areas, such as image classification and natural language processing.
The Gaussian distribution is a continuous probability distribution that is often used to model real-world data. It is characterized by its mean and variance. The mean is the average value of the data, and the variance is a measure of how spread out the data is.
The Gaussian distribution is a good model for many types of data, including height, weight, and temperature. It is also used in many statistical and machine learning algorithms.
The other options are incorrect because they are not types of distributions. Discrete distributions are distributions that can take on only a finite number of values. Binary distributions are distributions that can take on only two values.