How to get the first canonical correlation from sklearn's CCA module?

Question

In scikit-learn for Python, there is a module call cross_decomposition with a canonical correlation analysis (CCA) class. I have been trying to figure out how to give the c

Answer 1

Well, with some help looking at the source code in pyrcca I managed to create this snippet of code to get out the first canonical correlation.

cca = CCA(n_components=1)
U_c, V_c = cca.fit_transform(U, V)

result = np.corrcoef(U_c.T, V_c.T)[0,1]

Hope this helps someone else.

Note: The pyrcca package mentioned above runs slightly quicker than sci-kit learn's, due to heavier usage of multi-core processing for anyone who was curious. Also they have implemented kernel CCA unlike sklearn.