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feature_importances doesn't work in iterated model #66

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Moelf opened this issue Aug 26, 2024 · 3 comments · Fixed by #67
Closed

feature_importances doesn't work in iterated model #66

Moelf opened this issue Aug 26, 2024 · 3 comments · Fixed by #67
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@Moelf
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Moelf commented Aug 26, 2024

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@ablaom
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ablaom commented Aug 30, 2024

Thanks for reporting. Yes, it looks to me that feature_importance method is not forwarded to the wrapper IteratedModel.

@ablaom ablaom transferred this issue from JuliaAI/MLJXGBoostInterface.jl Aug 30, 2024
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ablaom commented Aug 30, 2024

I think the same forwarding we have for the TunedModel wrapper works here.

@OkonSamuel OkonSamuel self-assigned this Aug 30, 2024
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ablaom commented Aug 30, 2024

@Moelf As a workaround, can you try feature_importances(fitted_params(mach_bdt).machine), assuming mach_bdt is the machine bound to your IteratedModel instance.

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3 participants