Ah that does make sense. I hadn't seen too many people using bootstrap for
cross-validation, though I'm having a hard time coming up with references
for other methods of cross-validating prediction error in my particular
case. I know that K-Fold is a really common approach, but it's unclear to
me how to turn, say, a set of 10-Fold prediction errors into a statistic.
Thus far I've been doing 100 bootstraps and taking the 5/95 percentiles of
prediction error, but I haven't found a resource that says I can do this
for K-fold cross validation as well, so I was sticking with bootstrap. If
anyone knows of such a reference (doesn't have to be for K-Fold, just
anything that covers convergence properties for cross validation methods),
I'd be very appreciative :)
Chris
From: Lars Buitinck <larsm...@gmail.com>
To: scikit-learn-general <scikit-learn-general@lists.sourceforge.net>
Cc:
Date: Tue, 8 Jul 2014 22:04:45 +0200
Subject: Re: [Scikit-learn-general] Is there a reference for the Bootstrap
iterator?
2014-07-08 21:33 GMT+02:00 Andreas Mueller <t3k...@gmail.com>:
> On Jul 8, 2014 8:40 PM, "Chris Holdgraf" <choldg...@berkeley.edu> wrote:
>>
>> Hey all - I know that Bootstrap has a billion papers on it, but I was
>> wondering if there's a specific paper one should reference if we've been
>> using the Bootstrap iterator (here). I can't find one on the page, and it
>> would be good to point to a paper that details convergence properties for
>> statistics etc.
>
> I would cite ESL as a good textbook. Is you want the original, look there.
Bootstrap actually just got deprecated because it does something quite
non-standard. The deprecation warning references a short video lecture
by ESL's authors which you might like to watch:
http://youtu.be/BzHz0J9a6k0?t=9m38s.
See also https://github.com/scikit-learn/scikit-learn/pull/3295.
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