Backwarding : An Overfitting Control for Genetic Programming in a Remote Sensing Application
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{robilliard:2001:EA,
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author = "Denis Robilliard and Cyril Fonlupt",
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title = "Backwarding : An Overfitting Control for Genetic
Programming in a Remote Sensing Application",
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booktitle = "Artificial Evolution 5th International Conference,
Evolution Artificielle, EA 2001",
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year = "2001",
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editor = "P. Collet and C. Fonlupt and J.-K. Hao and
E. Lutton and M. Schoenauer",
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volume = "2310",
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series = "LNCS",
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pages = "245--254",
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address = "Creusot, France",
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month = oct # " 29-31",
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publisher = "Springer Verlag",
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ISBN = "3-540-43544-1",
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DOI = "doi:10.1007/3-540-46033-0_20",
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keywords = "genetic algorithms, genetic programming",
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abstract = "Overfitting the training data is a common problem in
supervised machine learning. When dealing with a remote
sensing inverse problem, the PAR, over-fitting prevents
GP evolved models to be successfully applied to real
data. We propose to use a classic method of over
fitting control by the way of a validation set. This
allows to go backward in the evolution process in order
to retrieve previous, not yet over fitted models.
Although this {"}backwarding{"} method performs well on
academic benchmarks, there is not enough improvement to
deal with the PAR. A new backwarding criterion is then
derived using real satellite data and the knowledge of
plausible physical bounds for the PAR coefficient in
the geographical area that is monitored. This leads to
satisfactory GP models and drastically improved
images.",
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notes = "EA'01",
- }
Genetic Programming entries for
Denis Robilliard
Cyril Fonlupt
Citations