thanks, very informative.
On Mon, Aug 18, 2014 at 1:08 PM, Olivier Grisel <[email protected]> wrote: > Le 18 août 2014 09:57, "Arman Eshaghi" <[email protected]> a écrit : > > > > > thanks for the discussion. Could you please what the right way of using > boostraping for confidence interval calculation (or other statistics) would > be? I mean what would you do to get, as olivier said a "generic resampling > method to estimate variance or confidence intervals"? I'm under the > impression that I need to define my own function for this as it is > not exactly what I had in mind? > > For genericbootstrap confidence intervals you can use scikits.bootstrap (a > small separate project). I would personally be in favor of having such > tools in scipy.stats by default though. > > > Also it seems that shuffle and split (I call it permutation) is also an > iterator for cross-validation (same confusion about bootstraping)? > > Yes but contrary to our deprecated Bootstrap class, the shuffle & split > strategy is a standard way to prepare folds for cross validation. You can > see it as a generalization of iterated randomized k fold cross validation > where you decouple test fold size from the number of folds / iterations. > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > >
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