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Support for multi-output regressors #273

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janosh opened this issue Nov 25, 2019 · 1 comment
Open

Support for multi-output regressors #273

janosh opened this issue Nov 25, 2019 · 1 comment
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major enhancement v2.0 Issues and enhancements for upcoming major release v2.0

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@janosh
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janosh commented Nov 25, 2019

What's your stance on supporting multi-output regressors? Would enable use cases such as uncertainty estimation where the learner might predict both a mean and a variance.

This might not be that hard to implement. It would start with modifying this line in DFMLAdaptor.predict() and perhaps modifying the new output_col kwarg to also accept a list of strings, i.e. one name for each type of output the regressor generates.

@ardunn ardunn added major enhancement v2.0 Issues and enhancements for upcoming major release v2.0 labels Nov 25, 2019
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ardunn commented Nov 25, 2019

@janosh I'll have to think about this. My hesitation is that none of the current default configs support this action (i.e., will never produce multiple outputs) so the only people who'd be using it are those who are already making their own highly customized pipelines.

If it doesn't introduce too much code complexity and have one preset demonstrating this behavior, I'd be in favor of it. Since it's going to be a relatively large upgrade though, I'm marking this for the next major release.

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