sklearn.gaussian_process#
Gaussian process based regression and classification.
User guide. See the Gaussian Processes section for further details.
Gaussian process classification (GPC) based on Laplace approximation. |
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Gaussian process regression (GPR). |
Kernels#
A set of kernels that can be combined by operators and used in Gaussian processes.
Kernel which is composed of a set of other kernels. |
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Constant kernel. |
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Dot-Product kernel. |
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Exp-Sine-Squared kernel (aka periodic kernel). |
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The Exponentiation kernel takes one base kernel and a scalar parameter \(p\) and combines them via |
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A kernel hyperparameter's specification in form of a namedtuple. |
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Base class for all kernels. |
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Matern kernel. |
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Wrapper for kernels in sklearn.metrics.pairwise. |
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The |
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Radial basis function kernel (aka squared-exponential kernel). |
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Rational Quadratic kernel. |
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The |
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White kernel. |