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moved doc back from kern.src to kern
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"""
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In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters.
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:py:class:`GPy.kern.src.kern.Kern` is a generic kernel object inherited by more specific, end-user kernels used in models. It provides methods that specific kernels should generally have such as :py:class:`GPy.kern.src.kern.Kern.K` to compute the value of the kernel, :py:class:`GPy.kern.src.kern.Kern.add` to combine kernels and numerous functions providing information on kernel gradients.
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.. inheritance-diagram:: GPy.kern.src.kern.Kern
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:top-classes: GPy.core.parameterization.parameterized.Parameterized
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"""
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from .src.kern import Kern
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from .src.kern import Kern
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from .src.add import Add
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from .src.add import Add
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from .src.prod import Prod
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from .src.prod import Prod
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"""
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In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters.
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.. inheritance-diagram:: GPy.kern.src.kern.Kern
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:top-classes: GPy.core.parameterization.parameterized.Parameterized
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"""
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from . import psi_comp
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from . import psi_comp
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