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Gaussian kernel class.
model_remediation.min_diff.losses.GaussianKernel( kernel_length: complex = 0.1, **kwargs )
The Gaussian kernel is a mathematical tool that approximates a given distribution as a sum of gaussian distributions. This is particularly useful when we are trying to determine a distribution from a set of points.
Length (sometimes also called 'width') of the kernel.
The choice for kernel length should be influenced by the average distance of inputs. The smaller the distance, the smaller the kernel length likely needs to be for best performance. In general, a good first guess is the standard deviation of your predictions.
Named parameters that will be passed directly to the base
See paper for reference on how it can be used in MinDiff.