“In reality, a doctor doesn’t diagnose the flu just based on whether you have a fever; she takes a whole bunch of symptoms into account, including whether you have a cough, a sore throat, a runny nose, a headache, chills, and so on. So what we really need to compute is P(flu | fever, cough, sore throat, runny nose, headache, chills, … ). By Bayes’ theorem, we know that this is proportional to P(fever, cough, sore throat, runny nose, headache, chills, …| flu). But now we run into a problem. How are we supposed to estimate this probability? If each symptom is a Boolean variable (you either have it or you don’t) and the doctor takes n symptoms into account, a patient could have 2n possible combinations of symptoms.”