apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-30 14:35:15 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

[SSGPLVM] Learn prior parameters

Browse source
This commit is contained in:
Zhenwen Dai 2014-03-04 10:39:56 +00:00
parent 0f6004034e
commit 0258abf5c4
2 changed files with 8 additions and 3 deletions
Download patch file Download diff file Expand all files Collapse all files

5
GPy/models/ss_gplvm.py
View file

@ -48,11 +48,14 @@ class SSGPLVM(SparseGP):
if kernel is None:
kernel = kern.SSRBF(input_dim)
self.variational_prior = SpikeAndSlabPrior(pi=0.5) # the prior probability of the latent binary variable b
pi = np.empty((input_dim))
pi[:] = 0.5
self.variational_prior = SpikeAndSlabPrior(pi=pi) # the prior probability of the latent binary variable b
X = SpikeAndSlabPosterior(X, X_variance, gamma)
SparseGP.__init__(self, X, Y, Z, kernel, likelihood, inference_method, name, **kwargs)
self.add_parameter(self.X, index=0)
self.add_parameter(self.variational_prior)
def parameters_changed(self):
super(SSGPLVM, self).parameters_changed()