Model-building with interpolated temporal data

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@Article{McKay:2006:EI,

• author = "R. I. (Bob) McKay and Hoang Tuan Hao and Naoki Mori and Nguyen Xuan Hoai and Daryl Essam",
• title = "Model-building with interpolated temporal data",
• journal = "Ecological Informics",
• year = "2006",
• volume = "1",
• number = "3",
• pages = "259--268",
• month = nov,
• note = "4th International Conference on Ecological Informatics",
• keywords = "genetic algorithms, genetic programming, Linear interpolation, Modelling",
• ISSN = "1574-9541",
• URL = "http://sc.snu.ac.kr/PAPERS/ISEI4-108_McKay.pdf",
• DOI = "doi:10.1016/j.ecoinf.2006.02.005",
• size = "31 pages",
• 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.",
• 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