Learning Data Mining with Python - Second Edition

Naive Bayes algorithm

Looking back at our Bayes' theorem equation, we can use it to compute the probability that a given sample belongs to a given class. This allows the equation to be used as a classification algorithm.

With C as a given class and D as a sample in our dataset, we create the elements necessary for Bayes' theorem, and subsequently Naive Bayes. Naive Bayes is a classification algorithm that utilizes Bayes' theorem to compute the probability that a new data sample belongs to a particular class.

P(D) is the probability of a given data sample. It can be difficult to compute this, as the sample is a complex interaction between different features, but luckily it is constant across all classes. Therefore, we don't need to compute ...