An Efficient Approach to Sparse Linear Discriminant Analysis

  title={An Efficient Approach to Sparse Linear Discriminant Analysis},
  author={Luis Francisco S{\'a}nchez Merchante and Yves Grandvalet and G{\'e}rard Govaert},
We present a novel approach to the formulation and the resolution of sparse Linear Discriminant Analysis (LDA). Our proposal, is based on penalized Optimal Scoring. It has an exact equivalence with penalized LDA, contrary to the multi-class approaches based on the regression of class indicator that have been proposed so far. Sparsity is obtained thanks to a group-Lasso penalty that selects the same features in all discriminant directions. Our experiments demonstrate that this approach generates… CONTINUE READING
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