Description: a novel method for solving Canonical Cor-
relation Analysis (CCA) in a sparse convex framework using a least
squares approach. The presented method focuses on the scenario when
one is interested in (or limited to) a primal representation for the first
view while having a dual representation for the second view. Sparse
CCA (SCCA) minimises the number of features used in both the pri-
mal and dual projections while maximising the correlation between the
two views.
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SCCA.m
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