Linear discriminant analysis (LDA) is a classical method for dimensionality reduction, where vectors are sought to project data lower dimensional space optimal separability of classes. Several recent papers have outlined strategies, based on exploiting sparsity the vectors, performing LDA in high-dimensional setting number features exceeds observations data. However, many these proposed methods...