Jan7-13, 04:21 PM
I am looking into canonical correlation analysis recently, and trying to dig deeper into it.
So far, I know the advantages of canonical correlation analysis are that it capable of revealing correlation between two sets of multi-dimensional variables. It also reduces the risk of committing Type I error.
However, I don't know about its disadvantages, though I believe there must be some.
The following link is the slides of a conference paper: http://www.math.univ-toulouse.fr/~ig...rance_Vzla.pdf
The authors claimed that the disadvantages of CCA are: 1. Much information get lost; 2. Poor interpretation of the results. Nontheless, there are no explainations about them.
May I know what are the disadvantages of canonical correlation analysis? And what nature of CCA caused these disadvantages?
Many thanks in advance for your kindly help.
|Register to reply|
|microcanonical vs canonical vs grand canonical ensemble||Classical Physics||1|
|canonical/grand canonical ensemble||Advanced Physics Homework||0|
|Methods for correlation and error analysis (statistical)||Calculus & Beyond Homework||1|
|non-canonical versus canonical DNA segment||Biology||1|