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Multiple output regression #85

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ZenBoer opened this issue Aug 3, 2018 · 1 comment
Open

Multiple output regression #85

ZenBoer opened this issue Aug 3, 2018 · 1 comment

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@ZenBoer
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@ZenBoer ZenBoer commented Aug 3, 2018

Most regression models are hardcoded with learning method: Learn(F64Matrix observations, double[] targets), what if we had multiple predicted variables.
I want to add method Learn(F64Matrix observations, F64Matrix targets)

@mdabros
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@mdabros mdabros commented Aug 6, 2018

Hi @ZenBoer ,

I have considered to expand the learner interface to something like Learn(Tensor observations, Tensor targets), to support a wider range of problems. This would be most relevant for neural networks, since it is non-trivial to add multi-task learning for the tree-based methods. When Microsoft makes an official release of their Tensor type, I will probably extend the interfaces to use this type. However, I don't expect this to happen in the very near future.

In the meantime, if you are using neural networks for you application, I would suggest using CNTK sine this already supports multiple predicted variables.

best regards
Mads

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