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class
The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).
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This Bayes Network learning algorithm uses
conditional independence tests to find a skeleton, finds V-nodes and applies
a set of rules to find the directions of the remaining arrows.
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class
This Bayes Network learning algorithm uses genetic
search for finding a well scoring Bayes network structure.
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This Bayes Network learning algorithm uses a hill
climbing algorithm adding, deleting and reversing arcs.
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This Bayes Network learning algorithm uses a hill
climbing algorithm restricted by an order on the variables.
For more information see:
G.F.
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This Bayes Network learning algorithm uses a Look
Ahead Hill Climbing algorithm called LAGD Hill Climbing.
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This Bayes Network learning algorithm repeatedly
uses hill climbing starting with a randomly generated network structure and
return the best structure of the various runs.
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This Bayes Network learning algorithm uses the
general purpose search method of simulated annealing to find a well scoring
network structure.
For more information see:
R.R.
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This Bayes Network learning algorithm uses tabu
search for finding a well scoring Bayes network structure.
class
This Bayes Network learning algorithm determines
the maximum weight spanning tree and returns a Naive Bayes network augmented
with a tree.
For more information see:
N.