empty.graph(LETTERS[1:8])
#
# Bayesian network learned via Conditional Independence methods
#
# model:
# [A][B][C][D][E][F][G][H]
# nodes: 8
# arcs: 0
# undirected arcs: 0
# directed arcs: 0
# average markov blanket size: 0.00
# average neighbourhood size: 0.00
# average branching factor: 0.00
#
# learning algorithm: random/generated
# tests used in the learning procedure: 0
#
random.graph(LETTERS[1:8])
# <insert the description of a random graph here>
plot(random.graph(LETTERS[1:8]))
plot(random.graph(LETTERS[1:8], prob = 0.2))
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