Sparse PCA with False Discovery Rate Controlled Variable Selection

Jasin Machkour, Arnaud Breloy, Michael Muma +2

Sparse principal component analysis (PCA) aims at mapping large dimensional data to a linear subspace of lower dimension. By imposing loading vectors to be sparse, it performs the…