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[SSGPLVM] numerical stability

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This commit is contained in:
Zhenwen Dai 2014-03-04 12:06:41 +00:00
parent 5c82fe39b9
commit 0f37cc721b
3 changed files with 7 additions and 5 deletions
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4
GPy/core/parameterization/variational.py
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@ -37,7 +37,7 @@ class SpikeAndSlabPrior(VariationalPrior):
def __init__(self, pi, variance = 1.0, name='SpikeAndSlabPrior', **kw):
super(VariationalPrior, self).__init__(name=name, **kw)
assert variance==1.0, "Not Implemented!"
self.pi = Param('pi', pi, Logistic(1e-10,1-1e-10))
self.pi = Param('pi', pi, Logistic(1e-10,1.-1e-10))
self.variance = Param('variance',variance)
self.add_parameters(self.pi)
@ -105,7 +105,7 @@ class SpikeAndSlabPosterior(VariationalPosterior):
binary_prob : the probability of the distribution on the slab part.
"""
super(SpikeAndSlabPosterior, self).__init__(means, variances, name)
self.gamma = Param("binary_prob",binary_prob, Logistic(1e-10,1-1e-10))
self.gamma = Param("binary_prob",binary_prob, Logistic(1e-10,1.-1e-10))
self.add_parameter(self.gamma)
def plot(self, *args):