mirror of
https://github.com/SheffieldML/GPy.git
synced 2026-05-05 01:32:40 +02:00
46ce7c1680
* Fix description of ExpQuad covariance. * Add sinc kernel. * Add ExpQuadCosine covariance
74 lines
3.4 KiB
Python
74 lines
3.4 KiB
Python
|
|
"""
|
|
Introduction
|
|
^^^^^^^^^^^^
|
|
|
|
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. *Note:
|
|
this may be too simple a definition for the broad range of kernels
|
|
available in :py:class:`GPy`.*
|
|
|
|
: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.
|
|
|
|
There are several inherited types of kernel that provide a basis for specific end user kernels:
|
|
|
|
.. inheritance-diagram:: GPy.kern.src.kern.Kern GPy.kern.src.static GPy.kern.src.stationary GPy.kern.src.kern.CombinationKernel GPy.kern.src.brownian GPy.kern.src.linear GPy.kern.src.standard_periodic
|
|
:top-classes: GPy.core.parameterization.parameterized.Parameterized
|
|
|
|
e.g. the archetype :py:class:`GPy.kern.RBF` does not inherit directly from :py:class:`GPy.kern.src.kern.Kern`, but from :py:class:`GPy.kern.src.stationary`.
|
|
|
|
.. inheritance-diagram:: GPy.kern.src.kern.Kern GPy.kern.RBF
|
|
:top-classes: GPy.core.parameterization.parameterized.Parameterized
|
|
|
|
"""
|
|
|
|
|
|
from .src.kern import Kern
|
|
from .src.add import Add
|
|
from .src.prod import Prod
|
|
from .src.rbf import RBF
|
|
from .src.linear import Linear, LinearFull
|
|
from .src.static import Bias, White, Fixed, WhiteHeteroscedastic, Precomputed
|
|
from .src.brownian import Brownian
|
|
from .src.stationary import Exponential, OU, Matern32, Matern52, ExpQuad, RatQuad, Cosine, Sinc, ExpQuadCosine
|
|
from .src.mlp import MLP
|
|
from .src.periodic import PeriodicExponential, PeriodicMatern32, PeriodicMatern52
|
|
from .src.standard_periodic import StdPeriodic
|
|
from .src.independent_outputs import IndependentOutputs, Hierarchical
|
|
from .src.coregionalize import Coregionalize
|
|
from .src.ODE_UY import ODE_UY
|
|
from .src.ODE_UYC import ODE_UYC
|
|
from .src.ODE_st import ODE_st
|
|
from .src.ODE_t import ODE_t
|
|
from .src.poly import Poly
|
|
from .src.eq_ode2 import EQ_ODE2
|
|
from .src.integral import Integral
|
|
from .src.integral_limits import Integral_Limits
|
|
from .src.multidimensional_integral_limits import Multidimensional_Integral_Limits
|
|
from .src.eq_ode1 import EQ_ODE1
|
|
from .src.trunclinear import TruncLinear,TruncLinear_inf
|
|
from .src.splitKern import SplitKern,DEtime
|
|
from .src.splitKern import DEtime as DiffGenomeKern
|
|
from .src.spline import Spline
|
|
from .src.basis_funcs import LogisticBasisFuncKernel, LinearSlopeBasisFuncKernel, BasisFuncKernel, ChangePointBasisFuncKernel, DomainKernel, PolynomialBasisFuncKernel
|
|
from .src.grid_kerns import GridRBF
|
|
from .src.symmetric import Symmetric
|
|
|
|
from .src.sde_matern import sde_Matern32
|
|
from .src.sde_matern import sde_Matern52
|
|
from .src.sde_linear import sde_Linear
|
|
from .src.sde_standard_periodic import sde_StdPeriodic
|
|
from .src.sde_static import sde_White, sde_Bias
|
|
from .src.sde_stationary import sde_RBF,sde_Exponential,sde_RatQuad
|
|
from .src.sde_brownian import sde_Brownian
|
|
from .src.multioutput_kern import MultioutputKern
|
|
from .src.multioutput_derivative_kern import MultioutputDerivativeKern
|
|
from .src.diff_kern import DiffKern
|