It describes formal structures in hyperspace invariant with respect to the rotation of their coordinates.
In this type of solution, rotation leaves many optimizing properties preserved, provided it takes place in certain ways and in a subspace of its corresponding hyperspace.
Canonical analysis is a multivariate technique which is concerned with determining the relationships between groups of variables in a data set.
The data set is split into two groups X and Y, based on some common characteristics.
(Tofallis, 1999) Mathematically, canonical analysis maximizes U′X′YV subject to U′X′XU = I and V′Y′YV = I, where X and Y are the data matrices (row for instance and column for feature).