The kernel estimator fits a local mean at each point x and thus cannot even estimate a line without bias (Cleveland, Cleveland, Devlin and Grosse 1988). An estimator based on locally-weighted ...
I've been using Savitzky-Golay (SG) filters for quite a while, but always on 1D data, using an implementation based on the algorithm from the Numerical Recipes to calculate the kernel (mask, ...
Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...
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