A Study of the Classification of Low-Dimensional Data with Supervised Manifold Learning.
Elif VuralChristine GuillemotPublished in: J. Mach. Learn. Res. (2017)
Keyphrases
- manifold learning
- low dimensional
- high dimensional data
- dimension reduction
- dimensionality reduction
- data sets
- high dimensional
- manifold structure
- nonlinear dimensionality reduction
- embedding space
- data analysis
- feature space
- data points
- input space
- decision trees
- machine learning
- subspace learning
- intrinsic manifold
- unsupervised learning
- input data
- semi supervised
- support vector machine
- pattern recognition
- feature selection
- neural network
- manifold learning algorithm
- underlying manifold
- diffusion maps
- low dimensional manifolds
- laplacian eigenmaps
- support vector
- dimensionality reduction methods
- geodesic distance
- nearest neighbor
- cluster analysis
- vector space