Semi-supervised linear discriminant analysis through moment-constraint parameter estimation

Marco Loog

Abstract: Highlights•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.