CCA stands for Canonical Correlation Analysis. It is a statistical technique used to identify and quantify the associations between two sets of multivariate variables. In simpler terms, CCA aims to find linear combinations of variables from each set that have the highest possible correlation with each other. It's used in fields like neuroscience, signal processing, and bioinformatics to find relationships between different datasets. For example, it can be used to find relationships between brain activity and behavior, or between gene expression levels and disease phenotypes.
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