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fixes to EP

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This commit is contained in:
James Hensman 2014-03-14 11:47:23 +00:00
parent 1ed7d73219
commit 77d08a7d6f
7 changed files with 36 additions and 32 deletions
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2
GPy/examples/classification.py
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@ -89,7 +89,7 @@ def toy_linear_1d_classification_laplace(seed=default_seed, optimize=True, plot=
likelihood = GPy.likelihoods.Bernoulli()
laplace_inf = GPy.inference.latent_function_inference.Laplace()
kernel = GPy.kern.rbf(1)
kernel = GPy.kern.RBF(1)
# Model definition
m = GPy.core.GP(data['X'], Y, kernel=kernel, likelihood=likelihood, inference_method=laplace_inf)

4
GPy/examples/regression.py
View file

@ -318,7 +318,7 @@ def toy_ARD(max_iters=1000, kernel_type='linear', num_samples=300, D=4, optimize
Y /= Y.std()
if kernel_type == 'linear':
kernel = GPy.kern.linear(X.shape[1], ARD=1)
kernel = GPy.kern.Linear(X.shape[1], ARD=1)
elif kernel_type == 'rbf_inv':
kernel = GPy.kern.RBF_inv(X.shape[1], ARD=1)
else:
@ -357,7 +357,7 @@ def toy_ARD_sparse(max_iters=1000, kernel_type='linear', num_samples=300, D=4, o
Y /= Y.std()
if kernel_type == 'linear':
kernel = GPy.kern.linear(X.shape[1], ARD=1)
kernel = GPy.kern.Linear(X.shape[1], ARD=1)
elif kernel_type == 'rbf_inv':
kernel = GPy.kern.RBF_inv(X.shape[1], ARD=1)
else: