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GPy/core/__init__.py
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Introduction
^^^^^^^^^^^^
This module contains the fundamental classes of GPy - classes that are inherited by objects in other parts of GPy in order to provide a consistent interface to major functionality.
This module contains the fundamental classes of GPy - classes that are
inherited by objects in other parts of GPy in order to provide a
consistent interface to major functionality.
.. inheritance-diagram:: GPy.core.gp.GP
:top-classes: paramz.core.parameter_core.Parameterizable
:py:class:`GPy.core.model` is inherited by :py:class:`GPy.core.gp.GP`. And :py:class:`GPy.core.model` itself inherits :py:class:`paramz.model.Model` from the `paramz` package. `paramz` essentially provides an inherited set of properties and functions used to manage state (and state changes) of the model.
:py:class:`GPy.core.model` is inherited by
:py:class:`GPy.core.gp.GP`. And :py:class:`GPy.core.model` itself
inherits :py:class:`paramz.model.Model` from the `paramz`
package. `paramz` essentially provides an inherited set of properties
and functions used to manage state (and state changes) of the model.
:py:class:`GPy.core.gp.GP` represents a GP model. Such an entity is typically passed variables representing known (x) and observed (y) data, along with a kernel and other information needed to create the specific model. It exposes functions which return information derived from the inputs to the model, for example predicting unobserved variables based on new known variables, or the log marginal likelihood of the current state of the model.
:py:class:`GPy.core.gp.GP` represents a GP model. Such an entity is
typically passed variables representing known (x) and observed (y)
data, along with a kernel and other information needed to create the
specific model. It exposes functions which return information derived
from the inputs to the model, for example predicting unobserved
variables based on new known variables, or the log marginal likelihood
of the current state of the model.
:py:func:`~GPy.core.gp.GP.optimize` is called to optimize hyperparameters of the model. The optimizer argument takes a string which is used to specify non-default optimization schemes.
:py:func:`~GPy.core.gp.GP.optimize` is called to optimize
hyperparameters of the model. The optimizer argument takes a string
which is used to specify non-default optimization schemes.
Various plotting functions can be called against :py:class:`GPy.core.gp.GP`.
.. inheritance-diagram:: GPy.core.gp_grid.GpGrid GPy.core.sparse_gp.SparseGP GPy.core.sparse_gp_mpi.SparseGP_MPI GPy.core.svgp.SVGP
:top-classes: GPy.core.gp.GP
:py:class:`GPy.core.gp.GP` is used as the basis for classes supporting more specialized types of Gaussian Process model. These are however generally still not specific enough to be called by the user and are inhereted by members of the :py:class:`GPy.models` package.
:py:class:`GPy.core.gp.GP` is used as the basis for classes supporting
more specialized types of Gaussian Process model. These are however
generally still not specific enough to be called by the user and are
inhereted by members of the :py:class:`GPy.models` package.
"""