https://d2l.ai/chapter_appendix-mathematics-for-deep-learning/naive-bayes.html

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?