Sparse Principal Component Analysis via Rotation and Truncation
Sparse Principal Component Analysis via Rotation and Truncation
Sparse principal component analysis (sparse PCA) aims at finding a sparse basis to improve the interpretability over the dense basis of PCA, while still covering the data subspace as much as possible. In contrast to most existing work that addresses the problem by adding sparsity penalties on various objectives of …