Inference of Bayesian Network
Total conditional probability is efficient (always) than Bayesian Netowrk?
If x1 is the only parent of y in Bayesian network, what can you say about P(y/x1, x2, x3)
Given network, (with (u,v) representing edge between u to v or parent of v is u), (p1,p2),(p2,p3),(p2,p4) and probabilites Pr(p1=T) = 0.4, Pr(p2=T/p1=T) = 0.8, Pr(p2=T/p1=F) = 0.5, Pr(p3=T/p2=T) = 0.2, Pr(p3=T/p2=F) = 0.3, Pr(p4=T/p2=T) = 0.8, Pr(p4=T/p2=F) = 0.5 Calculate Pr(p3=F)?
Given network, (with (u,v) representing edge between u to v or parent of v is u), (p1,p2),(p2,p3),(p2,p4) and probabilites Pr(p1=T) = 0.4, Pr(p2=T/p1=T) = 0.8, Pr(p2=T/p1=F) = 0.5, Pr(p3=T/p2=T) = 0.2, Pr(p3=T/p2=F) = 0.3, Pr(p4=T/p2=T) = 0.8, Pr(p4=T/p2=F) = 0.5 Calculate Pr(p2=T/p3=F)?
Given network, (with (u,v) representing edge between u to v or parent of v is u), (p1,p2),(p2,p3),(p2,p4) and probabilites Pr(p1=T) = 0.4, Pr(p2=T/p1=T) = 0.8, Pr(p2=T/p1=F) = 0.5, Pr(p3=T/p2=T) = 0.2, Pr(p3=T/p2=F) = 0.3, Pr(p4=T/p2=T) = 0.8, Pr(p4=T/p2=F) = 0.5 Calculate Pr(p1=T/p2=T,p3=F)?