SLISEMAP: supervised dimensionality reduction through local explanations.
Anton BjörklundJarmo MäkeläKai PuolamäkiPublished in: Mach. Learn. (2023)
Keyphrases
- supervised dimensionality reduction
- linear transformation
- least squares
- dimensionality reduction
- lower dimensional
- fisher discriminant analysis
- kernel trick
- linear discriminant analysis
- multimodal data
- dimensionality reduction methods
- scatter matrices
- discriminant analysis
- feature space
- input space
- maximum margin
- linear model
- discriminative learning
- high dimensional feature space
- singular value decomposition
- low dimensional
- support vector machine
- data points
- image processing