Canonical correlation analysis (CCA) is a natural generalization of PCA when the data contain two sets of variables (Hotelling, 1936). As in PCA, CCA also aims at simplifying the correlation structure between the two sets of variables by employing linear transformations. However, the presence of two sets of variables complicates the problem, as well as the notations.
Cannonical correlation analysis (CCA)
Michele Gallo
2021-01-01
Abstract
Canonical correlation analysis (CCA) is a natural generalization of PCA when the data contain two sets of variables (Hotelling, 1936). As in PCA, CCA also aims at simplifying the correlation structure between the two sets of variables by employing linear transformations. However, the presence of two sets of variables complicates the problem, as well as the notations.File in questo prodotto:
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