Biology Reference
In-Depth Information
Exercises
5.1.
Using the
hailfinder
data set included in
bnlearn
and a
snow
cluster with
at least 2 slave processes:
(a) Compute the number of levels and the most common level for each node.
(b) Split the samples among the slaves and identify which nodes have at least one
level with less than 5 observations in that particular subsample.
(c) Compute the entropy of each variable in
hailfinder
,definedas
)=
∑
−
p
log
p
,
H
(
p
where
p
is the relative frequency of each level of the variable.
5.2.
Consider the
alarm
data set included in
bnlearn
.
(a) Learn the structure of the network using Inter-IAMB and a shrinkage test with
alpha = 0.01
and measure the execution time of the algorithm.
(b) Does a 2-node cluster provide a greater performance improvement than just
switching from
optimized = FALSE
to
optimized = TRUE
?
(c) Is that still true when a Monte Carlo permutation test is used?
5.3.
Consider again the
alarm
data set from Exercise
5.2
,anda
snow
cluster with
at least 2 nodes.
(a) Use nonparametric bootstrap to determine the distribution of the number of arcs
present in a network structure learned with
hc
.
(b) How does that distribution change when bootstrap samples have size
m = 100
?
(c) Compare the distribution of the number of score comparisons for
m = 100
and
m = 5000
.
5.4.
Implement a parallel version of the model averaging performed using
hc
with
random starting networks in Sect.
2.5.1
.
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