Naive Bayes is a supervised machine learning algorithm that is used for classification tasks. It is based on the idea of applying Bayes' theorem using strong (naive) independence assumptions between the features.
This code will perform Naive Bayes classification on a set of training data points with three features (x1, x2, and x3) and labels of 0 or 1. It will calculate the prior probabilities for each label, as well as the conditional probabilities for each feature given each label.
What is Naive_Bayes? https://gefi.io/index.php?title=Naive_Bayes