Hi all, Currently I have unbalanced samples in each run (unequal number of samples per condition).
If I do leave-one-run-out classification, am I correct to use the following partitioner in my classifier to ensure an equal number of samples per condition, for each classification fold? ChainNode([NFoldPartitioner(),Balancer(attr='targets',count=1,limit='partitions',apply_selection=True)],space='partitions')) Also, what happens if in some runs, I have no trials for a certain condition? I imagine that on folds where those runs are part of the "test dataset", this would be problematic (nothing to test against)? So are those fold entirely excluded from the analysis if I use Balancer? Thanks! -Edmund
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