Skip to main content


Showing posts with the label CCA

Exploring Canonical Correlation Analysis (CCA): Uncovering Hidden Relationships

Canonical Correlation Analysis (CCA) is a statistical technique that enables us to uncover hidden associations between two sets of variables. Whether it's in the fields of psychology, economics, genetics, marketing or machine learning, CCA proves to be a powerful tool for gaining valuable insights. In this blog post, we will try to understand CCA. But first let’s take a look at two sets of observations, X and Y , shown below. These two sets of observations are made on the same set of objects and each observation represents a different variable. Let’s calculate pairwise correlation between the column vectors of X and Y . The resulting correlation values should give us some insight between the two sets of measurements. These values are shown below where the entry at (i,j) represents the correlation between the i-th column of X and the j-th column of Y . The correlation values show moderate to almost no correlation between the columns of the two datasets except a relatively higher