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allowing set initial noise variance for GPRegression

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javiergonzalezh 2015-06-15 18:42:29 +01:00
parent 24e759199e
commit e58cc51c47
1 changed files with 4 additions and 3 deletions
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5
GPy/models/gp_regression.py
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@ -16,6 +16,7 @@ class GPRegression(GP):
:param Y: observed values :param Y: observed values
:param kernel: a GPy kernel, defaults to rbf :param kernel: a GPy kernel, defaults to rbf
:param Norm normalizer: [False] :param Norm normalizer: [False]
:param noise_var: the noise variance for Gaussian likelhood, defaults to 1.
Normalize Y with the norm given. Normalize Y with the norm given.
If normalizer is False, no normalization will be done If normalizer is False, no normalization will be done
@ -25,12 +26,12 @@ class GPRegression(GP):
""" """
def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=None): def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=None, noise_var=1.):
if kernel is None: if kernel is None:
kernel = kern.RBF(X.shape[1]) kernel = kern.RBF(X.shape[1])
likelihood = likelihoods.Gaussian() likelihood = likelihoods.Gaussian(variance=noise_var)
super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression', Y_metadata=Y_metadata, normalizer=normalizer) super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression', Y_metadata=Y_metadata, normalizer=normalizer)