GPy/GPy/models/gp_regression.py

36 lines
957 B
Python

# Copyright (c) 2012 - 2014 the GPy Austhors (see AUTHORS.txt)
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
from ..core import GP
from .. import likelihoods
from .. import kern
class GPRegression(GP):
"""
Gaussian Process model for regression
This is a thin wrapper around the models.GP class, with a set of sensible defaults
:param X: input observations
:param Y: observed values
:param kernel: a GPy kernel, defaults to rbf
.. Note:: Multiple independent outputs are allowed using columns of Y
"""
def __init__(self, X, Y, kernel=None):
if kernel is None:
kernel = kern.rbf(X.shape[1])
likelihood = likelihoods.Gaussian()
super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression')
def _getstate(self):
return GP._getstate(self)
def _setstate(self, state):
return GP._setstate(self, state)