Variable selection for nonlinear dimensionality reduction of biological datasets through bootstrapping of correlation networks.
David G. AragonesMiguel Palomino-SeguraJon SiciliaGeorgiana CrainiciucIván BallesterosFátima Sánchez-CaboAndrés HidalgoGabriel Fernández CalvoPublished in: Comput. Biol. Medicine (2024)
Keyphrases
- variable selection
- nonlinear dimensionality reduction
- high dimensional data
- high dimensional
- manifold learning
- dimension reduction
- low dimensional
- dimensionality reduction
- input variables
- cross validation
- locally linear embedding
- data sets
- model selection
- pattern recognition
- data points
- ls svm
- text mining
- linear discriminant analysis
- nearest neighbor
- similarity measure
- sparse representation
- high dimensionality
- image data
- riemannian manifolds
- neural network