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Bayesian Networks
book

Bayesian Networks

by Marco Scutari, Jean-Baptiste Denis
June 2014
Intermediate to advanced content levelIntermediate to advanced
241 pages
6h 20m
English
CRC Press
Content preview from Bayesian Networks
Theory and Algorithms for Bayesian Networks 115
Algorithm 4.5 Logic Sampling Algorithm
1. Order the variables in X according to the topological partial order-
ing implied by G, say X
(1)
X
(2)
. . . X
(p)
.
2. Set n
E
= 0 and n
E,q
= 0.
3. For a suitably large number of samples x = (x
1
, . . . , x
p
):
(a) generate x
(i)
, i = 1, . . . , p from X
(i)
| Π
X
(i)
taking advantage of
the fact that, thanks to the topological ordering, by the time
we are considering X
i
we have already generated the values of
all its parents Π
X
(i)
;
(b) if x includes E, set n
E
= n
E
+ 1;
(c) if x includes both Q = q and E, set n
E,q
= n
E,q
+ 1.
4. Estimate Pr(Q | E, G, Θ) with n
E,q
/n
E
.
of the query ...
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Publisher Resources

ISBN: 9781482225587