Effects of species prevalence on the performance of predictive models
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DOI: 10.1016/j.ecolmodel.2017.03.006
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References listed on IDEAS
- Lencioni, Valeria & Maiolini, Bruno & Marziali, Laura & Lek, Sovan & Rossaro, Bruno, 2007. "Macroinvertebrate assemblages in glacial stream systems: A comparison of linear multivariate methods with artificial neural networks," Ecological Modelling, Elsevier, vol. 203(1), pages 119-131.
- Stokland, Jogeir N. & Halvorsen, Rune & Støa, Bente, 2011. "Species distribution modelling—Effect of design and sample size of pseudo-absence observations," Ecological Modelling, Elsevier, vol. 222(11), pages 1800-1809.
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Cited by:
- Lu, Na & Niu, Jun & Kang, Shaozhong & Singh, Shailesh Kumar & Du, Taisheng, 2021. "A hybrid PCA-SEM-ANN model for the prediction of water use efficiency," Ecological Modelling, Elsevier, vol. 460(C).
- Simon, Alois & Katzensteiner, Klaus & Wallentin, Gudrun, 2023. "The integration of hierarchical levels of scale in tree species distribution models of silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.) in mountain forests," Ecological Modelling, Elsevier, vol. 485(C).
- Caradima, Bogdan & Scheidegger, Andreas & Brodersen, Jakob & Schuwirth, Nele, 2021. "Bridging mechanistic conceptual models and statistical species distribution models of riverine fish," Ecological Modelling, Elsevier, vol. 457(C).
- Benkendorf, Donald J. & Schwartz, Samuel D. & Cutler, D. Richard & Hawkins, Charles P., 2023. "Correcting for the effects of class imbalance improves the performance of machine-learning based species distribution models," Ecological Modelling, Elsevier, vol. 483(C).
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Keywords
Quadratic effect; Species occurrence; Logistic regression; Random forest; Artificial neural network; Support vector machine; Macroinvertebrates; Habitat suitability; Mekong river;All these keywords.
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