An evaluation framework for dimensionality reduction through sectional curvature.
Raúl Lara-CabreraÁngel González-PrietoDiego Pérez-LópezDiego TrujilloFernando OrtegaPublished in: CoRR (2023)
Keyphrases
- dimensionality reduction
- high dimensional data
- low dimensional
- feature selection
- principal component analysis
- data representation
- high dimensional
- multiscale
- data points
- principal components
- high dimensionality
- structure preserving
- pattern recognition
- pattern recognition and machine learning
- feature space
- linear discriminant analysis
- euclidean distance
- feature extraction
- scale space
- dimensionality reduction methods
- random projections
- manifold learning
- input space
- lower dimensional
- circular arcs
- d objects
- image segmentation
- curvature estimation
- evaluation framework
- machine learning
- cubic spline
- linear dimensionality reduction
- neural network
- supervised dimensionality reduction
- gaussian curvature
- planar curves
- kernel learning
- metric learning
- dimension reduction
- computer vision