Numerical Computing with Python

Understanding Bayes theorem with conditional probability

Conditional probability provides a way of calculating relationships between dependent events using Bayes theorem. For example, A and B are two events and we would like to calculate P(A\B) can be read as the probability of an event occurring A given the fact that event B already occurred, in fact, this is known as conditional probability, the equation can be written as follows:

To understand better, we will now talk about the email classification example. Our objective is to predict whether an email is a spam given the word lottery and some other clues. In this case, we already knew the ...