calculate the posterior probability of an event occuring given that some other event has occured from the likelihood, prior probability, and normalizing constant (evidence) of those events.

Naive bayes classifiers work with Bayes’ Theorem. Where we can calculate the posterior probability of an event occuring given that some other event has occured from the likelihood, prior probability, and normalizing constant (evidence) of those events. Bayes’ theorem Before constructing any model, let’s begin by opening the data file provided to you in the instructions to familiarize ourselves with the data we are going to be working with. The class label in our datasets will always be the left most column, in this case play. 1. What are the features that are

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