Conditional canonical correlation estimation based on covariates with random forests

2 code implementations • 23 Nov 2020 • Cansu Alakus, Denis Larocque, Sebastien Jacquemont, Fanny Barlaam, Charles-Olivier Martin, Kristian Agbogba, Sarah Lippe, Aurelie Labbe

We propose a new method called Random Forest with Canonical Correlation Analysis (RFCCA) to estimate the conditional canonical correlations between two sets of variables given subject-related covariates.

EEG