I just made an implementation of P(A|B)/P(¬A|B) for a "people who bought this also bought..." algorithm.
I'm doing it by
P(A|B) = count_users(bought_A_and_B)/count_users(bought_A) P(¬A|B) = count_users(bought_B_but_not_A)/count_users(did_not_buy_A)
Then dividing the top one by the bottom one I get a score which makes absolute sense, but what kind of correlation am I calculating? What is this method called? Where can I read more about it?
[EDIT] This is not for using in a production environment, it is just some algorithm which appeared out of the blue in an online course I'm taking, I was just wondering where it could come from. Also, when the number of users who bought item B but not item A is zero I just skip the pair until I get more data. The same goes on when the number of users who bought A is zero.