Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes

  title={Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes},
  author={Luis Rueda and B. John Oommen and Claudio Henr{\'i}quez},
  journal={Pattern Recognition},
Linear Dimensionality Reduction (LDR) techniques have been increasingly important in Pattern Recognition (PR) due to the fact that they permit a relatively simple mapping of the problem onto a lower-dimensional subspace, leading to simple and computationally efficient classification strategies. Although the field has been well developed for the two-class problem, the corresponding issues encountered when dealing with multiple classes are far from trivial. In this paper, we argue that, as… CONTINUE READING
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