# Previous ChapterChapter 7: Canonical Correlation Next Chapter

Chapter 7: Canonical Correlation

Canonical Correlation
Canonical correlation
Introduction

A canonical correlation is the correlation of two canonical (latent) variables, one representing a set of independent variables, the other a set of dependent variables. Each set may be considered a latent variable based on measured indicator variables in its set. The canonical correlation is optimized such that the linear correlation between the two latent variables is maximized. Whereas multiple regression is used for many-to-one relationships, canonical correlation is used for many-to-many relationships. There may be more than one such linear correlation relating the two sets of variables, with each such correlation representing a different dimension by which the independent set of variables is related to the dependent set. The purpose of canonical correlation is to explain the relation of the two ...