It's not really clear to me what you want to achieve. What do you mean by "does not lead to a biased accuracy"?
On 09/26/2016 05:06 PM, Afarin Famili wrote:
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
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