Summary
n Employed Active Learning for causal structure in
Bayesian Networks
n Efficient algorithm
n Closed form computation for fixed ordering
n Use of graphical model inference to perform exponential
computation
n MCMC samples of orderings
n Experimental results show that Active Learning can
reduce the number of instances required