A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape
A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape
作者
关键词
Random forests, Artificial neural networks, Support vector regression, Soil organic carbon, Digital soil mapping, Eastern Mau, Kenya
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