Feature-space selection with banded ridge regression

Tom Dupré la Tour, Michael Eickenberg, Anwar Nunez-Elizalde, Jack L. Gallant

Abstract: Highlights•Using multiple feature spaces in a joint encoding model improves prediction accuracy.•The variance explained by the joint model can be decomposed over feature spaces.•Banded ridge regression optimizes the regularization for each feature space.•Banded ridge regression contains an implicit feature-space selection mechanism.•Banded ridge regression can be solved with random search or gradient descent.