On Mon, 30 Dec 2013, Adam Riggall wrote:

>    In doc/source/tutorial_start.rst:

>  >  :term:`sample` came from *even* or *odd* runs.  We ran the classification
>  >  analysis on each split to estimate the performance of the
>  >  classifier model. In general, this approach is called :term:`cross-validation`,
>  > -and involves splitting the dataset in multiple pairs of subsets, choosing
>  > +and involves splitting the dataset into multiple pairs of subsets, choosing

>    Another one I spent more time thinking on than I would like to admit! (The
>    first into two -> in two, actually) :-)

>    In the end I differed to here:
>    [1]http://english.stackexchange.com/questions/75153/split-in-vs-split-into
>    and
>    [2]http://english.stackexchange.com/questions/108335/split-in-half-vs-split-in-two-which-one-is-correct

>    In the first case we are dividing the data in half, so it's 'in', in the
>    second case we don't know the piece sizes, so it's 'into'.

thanks!  now I know about that beautiful Google Books Ngram Viewer) ;-)

my take here would be not really about sizes but rather it is 'how
action is performed' (split IN half) vs transformation ([transform]
dataset into multiple pairs ...).  Definite size is probably just a
coincidence, e.g.  I would have still said "split into equally-sized
sections" -- or do you feel that "split in equally-sized sections" would
be preferable then?

-- 
Yaroslav O. Halchenko, Ph.D.
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Senior Research Associate,     Psychological and Brain Sciences Dept.
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