What if you split the data pairwise(i.e. X_success, X_fail, etc) with subjects
matched by row index, then run train_test_split on each one with the same
random_state?
Naoya Kanai
Sent from
https://polymail.io/
On Mon, Sep 26, 2016 at 2:06 PM Afarin Famili
<
mailto:Afarin Famili <afarin.fam...@utsouthwestern.edu>
> wrote:
a, pre, code, a:link, body { word-wrap: break-word !important; }
Hi David,
When applying Train_test_split to the sample space, we have a single row per
subject. I am looking for some other function like Train_test_split that can
deal with pairs of rows (for each subject), which does not lead to a biased
accuracy. We are studying memory and have a row of features for successful
memory encoding, and a second row for unsuccessful memory encoding in each of
the subjects. Our target space being 1 for successful and 0 for unsuccessful
encoding respectively.
How do you recommend me to split this set of data in order to get a
reasonable/unbiased accuracy?
Thanks,
Afarin
________________________________________
From: scikit-learn
mailto:utsouthwestern....@python.org_______________________________________________
scikit-learn mailing list
scikit-learn@python.org
https://mail.python.org/mailman/listinfo/scikit-learn
