Semi-supervised linear discriminant analysis through moment-constraint parameter estimation
Semi-supervised learning can lead to worse performance with more unlabeled data. A novel take on semi-supervised learning through intrinsic constraints is introduced. An affine invariant, constrained, semi-supervised approach to LDA is proposed. Extensive experiments show good performance and clear benefits of constrained LDA.
linear discriminant analysis semi-supervised learning affine invariant moment constraints classification