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minor changes

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This commit is contained in:
Ricardo Andrade 2013-03-22 19:03:46 +00:00
parent b007f7cda6
commit 35a099f4ed
2 changed files with 10 additions and 9 deletions
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4
GPy/examples/fitc_class_01.py
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@ -42,8 +42,8 @@ m.ensure_default_constraints()
m.update_likelihood_approximation()
print m.checkgrad(verbose=1)
# Parameters optimization:
m.optimize()
#m.EPEM() #FIXME
#m.optimize()
m.pseudo_EM() #FIXME
# Plot
pb.subplot(211)

15
GPy/examples/fitc_class_02.py
View file

@ -25,15 +25,15 @@ likelihood = GPy.likelihoods.EP(data['Y'],distribution)
sample = np.random.randint(0,data['X'].shape[0],10)
Z = data['X'][sample,:]
# create sparse GP EP model
#m = GPy.models.sparse_GP(data['X'],likelihood=likelihood,kernel=kernel,Z=Z)
m = GPy.models.generalized_FITC(data['X'],likelihood=likelihood,kernel=kernel,Z=Z)
m.ensure_default_constraints()
m.set('len',10.)
m.update_likelihood_approximation()
#m.update_likelihood_approximation()
# optimize
m.optimize()
#m.optimize()
m.pseudo_EM()
print(m)
# plot
@ -48,17 +48,18 @@ kernel = GPy.kern.rbf(data['X'].shape[1]) + GPy.kern.white(data['X'].shape[1])
distribution = GPy.likelihoods.likelihood_functions.probit()
likelihood = GPy.likelihoods.EP(data['Y'],distribution)
sample = np.random.randint(0,data['X'].shape[0],10)
Z = data['X'][sample,:]
#sample = np.random.randint(0,data['X'].shape[0],10)
#Z = data['X'][sample,:]
# create sparse GP EP model
m = GPy.models.sparse_GP(data['X'],likelihood=likelihood,kernel=kernel,Z=Z)
m.ensure_default_constraints()
m.set('len',10.)
m.update_likelihood_approximation()
#m.update_likelihood_approximation()
# optimize
m.optimize()
#m.optimize()
m.pseudo_EM()
print(m)
# plot