new GP_classification model

This commit is contained in:
Ricardo 2013-06-04 18:16:08 +01:00
parent 2e6bbbf12b
commit a87dd7296c
2 changed files with 5 additions and 2 deletions

View file

@ -62,7 +62,7 @@ def oil():
likelihood = GPy.likelihoods.EP(Y, distribution)
# Create GP model
m = GPy.models.GP(data['X'], likelihood=likelihood, kernel=kernel)
m = GPy.models.GP_classification(data['X'], Y, kernel=kernel)
# Contrain all parameters to be positive
m.constrain_positive('')
@ -93,9 +93,11 @@ def toy_linear_1d_classification(seed=default_seed):
link = GPy.likelihoods.link_functions.probit
distribution = GPy.likelihoods.likelihood_functions.binomial(link)
likelihood = GPy.likelihoods.EP(Y, distribution)
Y[1] = 1
# Model definition
m = GPy.models.GP(data['X'], likelihood=likelihood, kernel=kernel)
#m = GPy.models.GP(data['X'], likelihood=likelihood, kernel=kernel)
m = GPy.models.GP_classification(data['X'], Y, likelihood=likelihood, kernel=kernel)
m.ensure_default_constraints()
# Optimize