Comparison of general kernel, multiple kernel, infinite ensemble and semi-supervised support vector machines for landslide susceptibility prediction

Landslide susceptibility prediction is a key step in preventing and managing landslide hazards. As a classical supervised non-parametric machine learning model, support vector machine (SVM) has been widely used in landslide susceptibility prediction in recent years. However, most studies focus on th...

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