Pruning of genetic programming trees using permutation tests
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- @Article{Rockett:2020:EI,
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author = "Peter Rockett",
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title = "Pruning of genetic programming trees using permutation
tests",
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journal = "Evolutionary Intelligence",
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year = "2020",
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volume = "13",
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number = "4",
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pages = "649--661",
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keywords = "genetic algorithms, genetic programming, Permutation
testing, Tree pruning",
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URL = "https://rdcu.be/cU470",
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DOI = "doi:10.1007/s12065-020-00379-8",
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abstract = "We present a novel approach based on statistical
permutation tests for pruning redundant subtrees from
genetic programming (GP) trees that allows us to
explore the extent of effective redundancy. We observe
that over a range of regression problems, median tree
sizes are reduced by around 20percent largely
independent of test function, and that while some large
subtrees are removed, the median pruned subtree
comprises just three nodes; most take the form of an
exact algebraic simplification. Our statistically-based
pruning technique has allowed us to explore the
hypothesis that a given subtree can be replaced with a
constant if this substitution results in no statistical
change to the behavior of the parent tree--what we term
approximate simplification. In the eventuality, we
infer that more than 95percent of the accepted pruning
proposals are the result of algebraic simplifications,
which provides some practical insight into the scope of
removing redundancies in GP trees.",
- }
Genetic Programming entries for
Peter I Rockett
Citations