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[inference] rename wrong precision into variance

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Max Zwiessele 2016-09-01 13:16:50 +01:00
parent 898a9e3f15
commit 896887bd94
2 changed files with 5 additions and 5 deletions
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GPy/inference/latent_function_inference/expectation_propagation.py
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@ -66,7 +66,7 @@ class EP(EPBase, ExactGaussianInference):
#if we've already run EP, just use the existing approximation stored in self._ep_approximation
mu, Sigma, mu_tilde, tau_tilde, Z_tilde = self._ep_approximation
return super(EP, self).inference(kern, X, likelihood, mu_tilde[:,None], mean_function=mean_function, Y_metadata=Y_metadata, precision=1./tau_tilde, K=K, Z_tilde=np.log(Z_tilde).sum())
return super(EP, self).inference(kern, X, likelihood, mu_tilde[:,None], mean_function=mean_function, Y_metadata=Y_metadata, variance=1./tau_tilde, K=K, Z_tilde=np.log(Z_tilde).sum())
def expectation_propagation(self, K, Y, likelihood, Y_metadata):