Its a question from a test in machine learning. I have 3 binary variables x1,x2 and x3 (which means that each one of them can be either 1 or 0), each one of them has a binary output y (can be 0 or 1). for a general probabilistic classifier (it could be any probabilistic model except that its not a model that relies on Naive Bayes), how many parameters do we need in order to estimate it? you cant assume Naive Bayes independency
I saw that the answer is 16 but I dont know why I want to clarify that when I mean parameters I mean which Probability I will need such as P[Y=1] or P[X1=1|Y=1] ect'