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[MRG] Avoid uncessary copies in sklearn.preprocessing #13987

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merged 3 commits into from Jun 1, 2019

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@rth rth commented May 30, 2019

Partially addresses #13986

This removes the copy=True in the fit method of StandardScaler, MinMaxScaler, MaxAbsScaler, RobustScaler where it is typically not necessary to compute the scaling factors.

In practice, this makes StandardScaler().fit_transform 10%-20% faster on the few examples I have tried.

If that copy was necessary and this mistakenly removed it check_transformer_general(.., readonly_memmap=True) would fail in common tests.

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@NicolasHug NicolasHug left a comment

LGTM.

Looks like in these specific cases inplace would have been a more descriptive parameter name than copy, and might have prevented this.

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@thomasjpfan thomasjpfan left a comment

LGTM

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@thomasjpfan thomasjpfan commented May 30, 2019

Does this need a whats_new entry as an enhancement or a bug fix?

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@rth rth commented May 31, 2019

Thanks for the reviews! Added a what's new.

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@thomasjpfan thomasjpfan commented May 31, 2019

QuantileTransformer has a _check_inputs that copies during fit and transform. What you think about adding copy parameter to _check_inputs and setting it to false during fit and self.copy during transform?

@thomasjpfan thomasjpfan merged commit 9661a64 into scikit-learn:master Jun 1, 2019
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@thomasjpfan thomasjpfan commented Jun 1, 2019

Thank you @rth!

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3 participants