dss : list of datasets
Datasets to benchmark on. Usually a single dataset per subject.
hyper : Hyperalignment-like, optional
Beast which if called on a list of datasets should spit out trained
mappers. If not specified, `IdentityMapper`s will be used
part1 : Partitioner, optional
Partitioner to split data for hyperalignment “cross-validation”
part2 : Partitioner, optional
Partitioner for CV within the hyperalignment test split
window_size : int, optional
How many temporal points to consider for a classification sample
overlapping_windows : bool, optional
Strategy to how create and classify “samples” for classification. If
True – window_size samples from each time point (but trailing ones)
constitute a sample, and upon “predict” window_size of samples around
each test point is not considered. If False – samples are just taken
(with training and testing splits) at window_size step from one to
another.
do_zscore : bool, optional
Perform zscoring (overall, not per-chunk) for each dataset upon
partitioning with part1
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