Summary
n
Employed Active Learning for causal structure in
Bayesian Networks
n
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
n
Experimental results show that Active Learning can
reduce the number of instances required