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[normalizer] first commit for normalizer in GPy

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Conflicts:
	GPy/core/sparse_gp.py
	GPy/models/bayesian_gplvm.py
This commit is contained in:
mzwiessele 2014-08-27 12:05:13 -07:00
parent 7ed0e70a46
commit 7ec0e75c0e
6 changed files with 101 additions and 24 deletions
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9
GPy/models/gp_regression.py
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@ -15,17 +15,22 @@ class GPRegression(GP):
:param X: input observations
:param Y: observed values
:param kernel: a GPy kernel, defaults to rbf
:param Norm normalizer: [False]
Normalize Y with the norm given.
If normalizer is False, no normalization will be done
If it is None, we use GaussianNorm(alization)
.. Note:: Multiple independent outputs are allowed using columns of Y
"""
def __init__(self, X, Y, kernel=None, Y_metadata=None):
def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=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', Y_metadata=Y_metadata)
super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression', Y_metadata=Y_metadata, normalizer=normalizer)