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Generalized canonical correlation
In statistics, the generalized canonical correlation analysis (gCCA), is a way of making sense of cross-correlation matrices between the sets of random variables when there are more than two sets. It is a generalization of the Principal component analysis (PCA) to more than two sets of random variables like a conventional CCA also does the same thing for only two sets.
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