deep

Current implementations of CCA cannot handle data structures where one would expect structured covariance for certain variables (e.g. brain regions can be expected to covary the more close they are spatially, behavioral variables can be aggregated to certain groups like cognition, psychopathology, drugs, etc.). There have been two attempts to solve this problem: Group Sparse Canonical Correlation

DeepCShuffle should have feature parity with the base shuffle node. Interface should be same/identical.