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bug fixed

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ICM-RBF is used as default Kernel, but the user should be able to define a multiple output kernel outside and pass it to the model.
This commit is contained in:
Ricardo Andrade 2015-11-26 18:45:09 +00:00
parent 60645b8b03
commit ca34f1a273
1 changed files with 1 additions and 1 deletions
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2
GPy/models/sparse_gp_coregionalized_regression.py
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@ -44,7 +44,7 @@ class SparseGPCoregionalizedRegression(SparseGP):
if kernel is None: if kernel is None:
kernel = kern.RBF(X.shape[1]-1) kernel = kern.RBF(X.shape[1]-1)
kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=1,name=kernel_name) kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=1,name=kernel_name)
#Likelihood #Likelihood
likelihood = util.multioutput.build_likelihood(Y_list,self.output_index,likelihoods_list) likelihood = util.multioutput.build_likelihood(Y_list,self.output_index,likelihoods_list)