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fixing EP and merging it with GP_regression

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Ricardo Andrade 2013-01-25 18:14:28 +00:00
parent b6ffb57263
commit 6a2e0a1fe5
7 changed files with 403 additions and 93 deletions
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11
GPy/examples/ep_fix.py
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@ -25,14 +25,15 @@ seed=default_seed
data = GPy.util.datasets.toy_linear_1d_classification(seed=seed)
likelihood = GPy.inference.likelihoods.probit(data['Y'][:, 0:1])
m = GPy.models.GP_EP2(data['X'],likelihood)
m = GPy.models.GP(data['X'],likelihood=likelihood)
#m.constrain_positive('var')
#m.constrain_positive('len')
#m.tie_param('lengthscale')
m.constrain_positive('var')
m.constrain_positive('len')
m.tie_param('lengthscale')
m.approximate_likelihood()
print m.checkgrad()
# Optimize and plot
#m.optimize()
m.optimize()
#m.em(plot_all=False) # EM algorithm
m.plot()