The effect of number of queries and amount of evidence on the trade-off between clique tree propagation and variable elimination
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2021-06-18
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en
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Abstract
Two exact algorithms for inference in a Bayesian network (BN) are clique tree
propagation (CTP) and variable elimination (VE). With CTP there are some pre-
computations, but after that multiple queries can be performed e ciently. VE has
no precomputation and irrelevant variables can be pruned. Processing evidence after
the precomputations generates extra cost for CTP. With VE evidence is just taken
into account during the query. So CTP is suited for multiple queries, because the cost
of the precomputations can be spread over the queries, and VE is suited for a single
query where the observations are all given. Within this thesis is investigated how this
trade-o relates to the number of queries and evidence. The algorithms were used for
queries in several networks with di erent amounts of observations. The time of the
processes before and during the queries was measured and the amortization period
was calculated, which is the amount of queries needed to make CTP more preferable
than VE. The number of nodes, the average degree and the average number of values
per variable all a ected the amortization period. When the values for these properties
were below 50, 3.5 and 3 respectively, this period was only a few queries. It increased
when the values increased and at some point VE would always be preferred. Having
evidence coming in made CTP more favorable; only when large parts of the network
became observed VE started to bene t from it. These results can give more insight
in the trade-o between the algorithms.
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Faculteit der Sociale Wetenschappen