Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets.
Henry KvingeElin FarnellMichael KirbyChris PetersonPublished in: CoRR (2018)
Keyphrases
- dimensionality reduction
- data sets
- high dimensionality
- unsupervised learning
- low dimensional
- high dimensional data
- high dimensional
- data analysis
- principal component analysis
- linear discriminant analysis
- pattern recognition
- feature extraction
- preprocessing step
- data representation
- data points
- dimensionality reduction methods
- random projections
- coarse to fine
- hierarchical tree
- principal components
- linear dimensionality reduction
- manifold learning
- singular value decomposition
- data reduction
- feature space
- hierarchical clustering algorithms
- pattern recognition and machine learning
- hierarchical classification
- dimension reduction
- case study
- database
- multiresolution