Model Selection and Overfitting in Genetic Programming: Empirical Study

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00231779" target="_blank" >RIV/68407700:21230/15:00231779 - isvavai.cz</a>
Result on the web
<a href="http://dl.acm.org/citation.cfm?id=2764678&CFID=715756301&CFTOKEN=65340477" target="_blank" >http://dl.acm.org/citation.cfm?id=2764678&CFID=715756301&CFTOKEN=65340477</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2739482.2764678" target="_blank" >10.1145/2739482.2764678</a>

Result language
angličtina
Original language name
Model Selection and Overfitting in Genetic Programming: Empirical Study
Original language description
Genetic Programming has been very successful in solving a large area of problems but its use as a machine learning algorithm has been limited so far. One of the reasons is the problem of overfitting which cannot be solved or suppresed as easily as in more traditional approaches. Another problem, closely related to overfitting, is the selection of the final model from the population. In this article we present our research that addresses both problems: overfitting and model selection. We compare severalways of dealing with ovefitting, based on Random Sampling Technique (RST) and on using a validation set, all with an emphasis on model selection. We subject each approach to a thorough testing on artificial and real?world datasets and compare them with the standard approach, which uses the full training data, as a baseline.
Czech name
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Czech description
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference (GECCO 2015)
ISBN
978-1-4503-3488-4
ISSN
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e-ISSN
—
Number of pages
2
Pages from-to
1527-1528
Publisher name
ACM
Place of publication
New York
Event location
Madrid
Event date
Jul 11, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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