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sparse gp with uncertain inputs

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Max Zwiessele 2014-03-03 15:08:54 +00:00
parent 0062a5b16f
commit 1284a0683f
1 changed files with 2 additions and 2 deletions
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GPy/models/sparse_gp_regression.py
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@ -88,7 +88,7 @@ class SparseGPRegressionUncertainInput(SparseGP):
# kern defaults to rbf (plus white for stability) # kern defaults to rbf (plus white for stability)
if kernel is None: if kernel is None:
kernel = kern.rbf(input_dim) + kern.white(input_dim, variance=1e-3) kernel = kern.RBF(input_dim) + kern.White(input_dim, variance=1e-3)
# Z defaults to a subset of the data # Z defaults to a subset of the data
if Z is None: if Z is None:
@ -99,5 +99,5 @@ class SparseGPRegressionUncertainInput(SparseGP):
likelihood = likelihoods.Gaussian() likelihood = likelihoods.Gaussian()
SparseGP.__init__(self, X, Y, Z, kernel, likelihood, X_variance=X_variance) SparseGP.__init__(self, X, Y, Z, kernel, likelihood, X_variance=X_variance, inference_method=VarDTC())
self.ensure_default_constraints() self.ensure_default_constraints()