Model-building with interpolated temporal data
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{McKay:2006:EI,
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author = "R. I. (Bob) McKay and Hoang Tuan Hao and
Naoki Mori and Nguyen Xuan Hoai and Daryl Essam",
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title = "Model-building with interpolated temporal data",
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journal = "Ecological Informics",
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year = "2006",
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volume = "1",
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number = "3",
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pages = "259--268",
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month = nov,
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note = "4th International Conference on Ecological
Informatics",
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keywords = "genetic algorithms, genetic programming, Linear
interpolation, Modelling",
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ISSN = "1574-9541",
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URL = "http://sc.snu.ac.kr/PAPERS/ISEI4-108_McKay.pdf",
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DOI = "doi:10.1016/j.ecoinf.2006.02.005",
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size = "31 pages",
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abstract = "Ecological data can be difficult to collect, and as a
result, some important temporal ecological datasets
contain irregularly sampled data. Since many temporal
modelling techniques require regularly spaced data, one
common approach is to linearly interpolate the data,
and build a model from the interpolated data. However,
this process introduces an unquantified risk that the
data is over-fitted to the interpolated (and hence more
typical) instances. Using one such irregularly-sampled
dataset, the Lake Kasumigaura algal dataset, we compare
models built on the original sample data, and on the
interpolated data, to evaluate the risk of mis-fitting
based on the interpolated data.",
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notes = "http://www.sciencedirect.com/science/journal/15749541",
- }
Genetic Programming entries for
R I (Bob) McKay
Tuan-Hao Hoang
Naoki Mori
Nguyen Xuan Hoai
Daryl Essam
Citations