Model uses the new HeteroscedasticGaussian likelihood

This commit is contained in:
Ricardo 2015-09-02 12:15:06 +01:00
parent 938cc49aed
commit 7a5872e11d

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@ -30,10 +30,7 @@ class GPHeteroscedasticRegression(GP):
kernel = kern.RBF(X.shape[1])
#Likelihood
#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)
likelihood = likelihoods.HeteroscedasticGaussian(Y_metadata)
super(GPHeteroscedasticRegression, self).__init__(X,Y,kernel,likelihood, Y_metadata=Y_metadata)