Statistics for Machine Learning

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 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 email is spam given the word lottery and some other clues. In this case we already knew the overall ...