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Spatial prediction of soil great groups by boosted regression trees using a limited point dataset in an arid region, southeastern Iran

(2014) GEODERMA. 232-234. p.148-163
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Keywords
Soil diagnostic horizons, Soil great groups, Limited dataset, Boosted regression tree, ALGORITHMS, CLASSIFICATION, VALIDATION, LOGISTIC-REGRESSION, ACCURACY, VALLEY, MAP

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Citation

Please use this url to cite or link to this publication:

Chicago
Jafari, Azam, Hossein Khademi, Peter Finke, Johan Van de Wauw, and Shamsollah Ayoubi. 2014. “Spatial Prediction of Soil Great Groups by Boosted Regression Trees Using a Limited Point Dataset in an Arid Region, Southeastern Iran.” Geoderma 232-234: 148–163.
APA
Jafari, A., Khademi, H., Finke, P., Van de Wauw, J., & Ayoubi, S. (2014). Spatial prediction of soil great groups by boosted regression trees using a limited point dataset in an arid region, southeastern Iran. GEODERMA, 232-234, 148–163.
Vancouver
1.
Jafari A, Khademi H, Finke P, Van de Wauw J, Ayoubi S. Spatial prediction of soil great groups by boosted regression trees using a limited point dataset in an arid region, southeastern Iran. GEODERMA. 2014;232-234:148–63.
MLA
Jafari, Azam, Hossein Khademi, Peter Finke, et al. “Spatial Prediction of Soil Great Groups by Boosted Regression Trees Using a Limited Point Dataset in an Arid Region, Southeastern Iran.” GEODERMA 232-234 (2014): 148–163. Print.
@article{4426590,
  author       = {Jafari, Azam and Khademi, Hossein and Finke, Peter and Van de Wauw, Johan and Ayoubi, Shamsollah},
  issn         = {0016-7061},
  journal      = {GEODERMA},
  keywords     = {Soil diagnostic horizons,Soil great groups,Limited dataset,Boosted regression tree,ALGORITHMS,CLASSIFICATION,VALIDATION,LOGISTIC-REGRESSION,ACCURACY,VALLEY,MAP},
  language     = {eng},
  pages        = {148--163},
  title        = {Spatial prediction of soil great groups by boosted regression trees using a limited point dataset in an arid region, southeastern Iran},
  url          = {http://dx.doi.org/10.1016/j.geoderma.2014.04.029},
  volume       = {232-234},
  year         = {2014},
}

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