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?
Also it seems that shuffle and split (I call it permutation) is also an iterator for cross-validation (same confusion about bootstraping)? On Mon, Aug 18, 2014 at 12:16 PM, Olivier Grisel <[email protected]> wrote: > But the sklearn.cross_validation.Bootstrap currently implemented in > sklearn is a cross validation iterator, not a generic resampling method to > estimate variance or confidence intervals. Don't be mislead by the name. If > we chose to deprecate and then remove this class, it's precisely because it > causes confusion. > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > >
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