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    Null-model validation of MLP input contribution analysis in ecology

    Watts, Michael J.; Worner, Susan P.
    Abstract
    A method is presented for applying a null-model analysis to the verification of the significance of the input neurons of Multi-Layer Perceptrons (MLP). This method was applied to a problem from ecology, namely the establishment of invasive insect pest species. Previous work has described how the MLP were trained to predict species establishment from climate data, and to identify which climatic factors are significant. The null-model analysis method described here was used to validate these predictions.
    Keywords
    null-model analysis; multi-layer perceptrons; species establishment; prediction
    Fields of Research
    0501 Ecological Applications
    Date
    2006-12
    Type
    Conference Contribution - Published (Conference Paper)
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    • Bio-Protection Research Centre [309]
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    HIS.2006.264946.pdf
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    © 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Citation
    Watts, M. J., & Worner, S. P. (2006). Null-model validation of MLP input contribution analysis in ecology. In Proceedings: Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006 (pp. 63-66). Los Alamitos, CA: IEEE Computer Society.
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