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[missing_data in sparse gp] can be extended towards missing_data handling in gp itself. Setting up gpy issue

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This commit is contained in:
Max Zwiessele 2014-10-09 10:34:01 +01:00
parent de801c9d29
commit 829e40b25c
5 changed files with 15 additions and 11 deletions
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3
GPy/examples/dimensionality_reduction.py
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@ -374,9 +374,6 @@ def bgplvm_simulation_missing_data(optimize=True, verbose=1,
m = BayesianGPLVM(Ymissing, Q, init="random", num_inducing=num_inducing,
kernel=k, missing_data=True)
m.X.variance[:] = _np.random.uniform(0,.1,m.X.shape)
m.likelihood.variance = .01
m.parameters_changed()
m.Yreal = Y
if optimize: