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How to construct a kernel for coregionalization approaches in multiple outputs.ipynb? #20

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@coderxulh

Hi, I am confused in reading the notebook for multiple output in GPy.
In notebook https://github.com/SheffieldML/notebook/blob/ddb2a70491221ceb92d34cc3b7dc8b94f382192c/GPy/multiple%20outputs.ipynb, "**" operator is used to indicate a tensor product between rbf kernel and the coregionalize matrix B. While in the latter Exercise 1, a kernel is constructed as
"kern = ((GPy.kern.RBF(1, variance=1, lengthscale=70)+
GPy.kern.Linear(1, 1, active_dims=[0])+
GPy.kern.White(1)+
GPy.kern.Bias(1, 1))
*GPy.kern.Coregionalize(1, output_dim=2, rank=1, active_dims=1, name='gender')
GPy.kern.Coregionalize(1, output_dim=3, rank=1, active_dims=2, name='event')
)"
with two "
" operator. I don't know if I miss some information or there are several mistakes.
Wish to receive your reply. :)

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