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Supporting bootstrap sampling as in sklearn #153

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hmishfaq opened this issue Jul 9, 2023 · 3 comments
Open

Supporting bootstrap sampling as in sklearn #153

hmishfaq opened this issue Jul 9, 2023 · 3 comments

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@hmishfaq
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hmishfaq commented Jul 9, 2023

I am trying to convert a sklearn based code that uses sklearn.ensemble.BaggingRegressor and am wondering if Ensemble-pytorch can have bootstrap argument as sklearn has.

@xuyxu
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xuyxu commented Jul 9, 2023

Hi @hmishfaq, could you further explain which argument do you want to use. Currently, the Bagging estimators in Ensemble-pytorch only use the sample data with replacement technique.

@hmishfaq
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hmishfaq commented Jul 9, 2023

Hi @xuyxu, I would like to use the argument bootstrap as described in the link above of sklearn.ensemble.BagginRegressor. However, it seems there is no analog of such argument in ensemble-pytorch.

bootstrap:bool, default=True
Whether samples are drawn with replacement. If False, sampling without replacement is performed.

@xuyxu
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xuyxu commented Jul 9, 2023

This argument equals True in BaggingRegressor internally.

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