Conceptually, what would be the meaning of performing PCA on the $M'$ of initial matrix $M=[n \times m]$ where $n$ rows refer to observations and $m$ columns refer to variables?
Perform PCA for $N=10$ observations of a network/graph $G_n=[p \times p]$. PCA has been performed on $M'$ where $M= [N \times p^2]$, where each $G_n$ has been put into $M$ by vectorisation.
[U S V] = svd(cov(M')) PC = U'*M
By convention the columns indicate different variables, and the rows the different observations but I performed PCA on the transposed matrix and interesting results came up. Are these by any chance interpretable, or just meaningless?