Symbolic-regression boosting
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- @Article{Sipper_Moore:GPEM,
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author = "Moshe Sipper and Jason H. Moore",
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title = "Symbolic-regression boosting",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2021",
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volume = "22",
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number = "3",
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pages = "357--381",
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month = sep,
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keywords = "genetic algorithms, genetic programming, Symbolic
regression, Gradient boosting",
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ISSN = "1389-2576",
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URL = "https://rdcu.be/cFCTA",
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DOI = "doi:10.1007/s10710-021-09400-0",
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size = "25 pages",
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abstract = "Modifying standard gradient boosting by replacing the
embedded weak learner in favor of a strong(er) one, we
present SyRBo: symbolic-regression boosting.
Experiments over 98 regression datasets show that by
adding a small number of boosting stages, between 2 and
5, to a symbolic regressor, statistically significant
improvements can often be attained. We note that coding
SyRBo on top of any symbolic regressor is
straightforward, and the added cost is simply a few
more evolutionary rounds. SyRBo is essentially a simple
add-on that can be readily added to an extant symbolic
regressor, often with beneficial results.",
- }
Genetic Programming entries for
Moshe Sipper
Jason H Moore
Citations