Naive Bayes

I am unable to understand the below equation , can anyone explain ?

p_xy = P_xy * x + (1 - P_xy)*(1 - x)

If x=1, p_xy = P_xy
If x=0, p_xy = 1-P_xy
Just 18.9.5

“explain why allowing explicit dependence between the two input variables in the XOR model allows for the creation of a successful classifier.”
Is it about Naive Bayes Classifier? Is question about another Bayesian model where we could allow partion dependence between variables?