Sparse dimension reduction based on energy and ball statistics.
Emmanuel Jordy MenvoutaSven SerneelsTim VerdonckPublished in: Adv. Data Anal. Classif. (2022)
Keyphrases
- dimension reduction
- high dimensional
- random projections
- sparse metric learning
- feature extraction
- principal component analysis
- data mining and machine learning
- high dimensional data
- high dimensional problems
- variable selection
- feature selection
- high dimensionality
- low dimensional
- singular value decomposition
- manifold learning
- feature space
- discriminative information
- partial least squares
- high dimensional data analysis
- dimension reduction methods
- preprocessing
- dimensionality reduction
- sparse representation
- unsupervised learning
- learning algorithm
- knowledge discovery
- feature subspace
- intrinsic dimension
- cluster analysis