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Gboluwaga Lawrence Akande

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

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Improving Soil Property Mapping Using Support Vector Machines, Neural Networks, Gradient Boosted Trees and Random Forests Over Soils in Sub-Saharan Africa

Number of pages: 37 Posted: 26 Apr 2022
Gboluwaga Lawrence Akande, Ayodele Ajayi and Oluwaseun Temitope Faloye
affiliation not provided to SSRN, Federal University of Technology Akure and affiliation not provided to SSRN
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Citation 6

Abstract:

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spatial prediction, Sub-Saharan Africa, Gradient boosted trees, Neural network, Random Forest, Support vector machine