Spatial Analysis Made Easy with Linear Regression and Kernels
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DOI: 10.1016/j.epidem.2019.100362
Abstract: Kernel methods are a popular technique for extending linear models to handle non-linear spatial problems via a mapping to an implicit, high-dimensional feature space. While kernel methods are computationally cheaper than an explicit feature mapping,… read more here.
Keywords: regression; easy linear; kernel methods; spatial analysis ... See more keywords