bnlearn (version 2.0)

compare: Compare two different Bayesian networks

Description

Compare two different Bayesian networks or compute the Structural Hamming Distance (SHD) between them.

Usage

compare(r1, r2, debug = FALSE)
shd(learned, true, debug = FALSE)

Arguments

r1, learned

an object of class bn.

r2, true

another object of class bn.

debug

a boolean value. If TRUE a lot of debugging output is printed; otherwise the function is completely silent.

Value

• A boolean value: TRUE if the objects describe the same network structure, FALSE otherwise.

References

Tsamardinos I, Brown LE, Aliferis CF (2006). "The Max-Min Hill-Climbing Bayesian Network Structure Learning Algorithm". Machine Learning, 65(1), 31-78.

Examples

data(learning.test)

res = gs(learning.test)
## the arc between A and B has no direction
plot(res, highlight = c("A", "B"))
res2 = set.arc(res, "A", "B")
compare(res, res2, debug = TRUE)
# * children of A in r1 not present in r2:
# character(0)
# * children of A in r2 not present in r1:
# [1] "B"
# * parents of B in r1 not present in r2:
# character(0)
# * parents of B in r2 not present in r1:
# [1] "A"
# * directed arcs in r1 not present in r2:
# character(0)
# * directed arcs in r2 not present in r1:
# [1] "A -> B"
# * undirected arcs in r1 not present in r2:
# [1] "A - B" "B - A"
# * undirected arcs in r2 not present in r1:
# character(0)
# [1] FALSE
e1 = model2network("[A][B][C|A:B][D|B][E|C][F|A:E]")
e2 = model2network("[A][B][C|A:B][D|B][E|C:F][F|A]")
shd(e2, e1, debug = TRUE)
# * arcs between A and F do not match.
# * arcs between E and F do not match.
# [1] 2