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new GP_classification model

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Ricardo 2013-06-04 18:16:08 +01:00
parent 2e6bbbf12b
commit a87dd7296c
2 changed files with 5 additions and 2 deletions
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6
GPy/examples/classification.py
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@ -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

1
GPy/models/__init__.py
View file

@ -5,6 +5,7 @@
#from GP import GP
#from sparse_GP import sparse_GP
from GP_regression import GP_regression
from GP_classification import GP_classification
from sparse_GP_regression import sparse_GP_regression
from GPLVM import GPLVM
from warped_GP import warpedGP