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Noise parameters built depending on Y_metadata

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Ricardo 2014-08-26 17:06:09 +01:00
parent ac61282e11
commit 993c3421f4
1 changed files with 3 additions and 1 deletions
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GPy/models/gp_heteroscedastic_regression.py
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@ -30,7 +30,9 @@ class GPHeteroscedasticRegression(GP):
kernel = kern.RBF(X.shape[1])
#Likelihood
likelihoods_list = [likelihoods.Gaussian(name="Gaussian_noise_%s" %j) for j in range(Ny)]
#likelihoods_list = [likelihoods.Gaussian(name="Gaussian_noise_%s" %j) for j in range(Ny)]
noise_terms = np.unique(Y_metadata['output_index'].flatten())
likelihoods_list = [likelihoods.Gaussian(name="Gaussian_noise_%s" %j) for j in noise_terms]
likelihood = likelihoods.MixedNoise(likelihoods_list=likelihoods_list)
super(GPHeteroscedasticRegression, self).__init__(X,Y,kernel,likelihood, Y_metadata=Y_metadata)