8000 Collapsing PCA and RandomizedPCA · Issue #5243 · scikit-learn/scikit-learn · GitHub
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giorgiop opened this issue Sep 10, 2015 · 6 comments · Fixed by #5299
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Collapsing PCA and RandomizedPCA #5243

giorgiop opened this issue Sep 10, 2015 · 6 comments · Fixed by #5299

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@giorgiop
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Following discussions in #5141 we may want to collapse RandomizedPCA as an alternative solver into PCA with a svd_solver='auto' that would use randomized_svd whenever n_components + n_oversamples < 0.8 * min(n_samples, n_features).

This reflects the implementation of fbpca. People may not know that RandomizedPCA exists or when it makes sense to use it.
@amueller
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+1

@kastnerkyle
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I think it is a good idea - +1

On Thu, Sep 10, 2015 at 9:53 AM, Andreas Mueller notifications@github.com
wrote:

+1

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@jakevdp
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jakevdp commented Sep 10, 2015

+1 – though of course we'd want to leave RandomizedPCA around as a wrapper for a couple releases.

@larsmans
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+1

@giorgiop
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Any idea on how to handle the options n_components in (0,1) and 'mle'? Those are used after computing the SVD. I also want to start supporting scipy.sparse.linalg.svds as a solver for truncated SVD. The issue is the same.

ValueError or something more clever?

@GaelVaroquaux
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GaelVaroquaux commented Sep 18, 2015 via email

@giorgiop giorgiop mentioned this issue Sep 23, 2015
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@giorgiop giorgiop mentioned this issue Oct 23, 2015
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[MRG+3] Collapsing PCA and RandomizedPCA giorgiop/scikit-learn
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@GaelVaroquaux @larsmans @amueller @jakevdp @kastnerkyle @giorgiop
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