UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.
Leland McInnesJohn HealyPublished in: CoRR (2018)
Keyphrases
- dimension reduction
- manifold learning
- low dimensional
- high dimensional
- manifold embedding
- nonlinear manifold
- principal component analysis
- feature space
- generative topographic mapping
- feature extraction
- manifold learning algorithm
- high dimensional problems
- high dimensional data
- random projections
- linear discriminant analysis
- singular value decomposition
- feature selection
- intrinsic dimension
- dimension reduction methods
- high dimensionality
- unsupervised learning
- dimensionality reduction
- preprocessing
- discriminative information
- manifold structure
- diffusion maps
- lower dimensional
- cluster analysis
- convex sets
- geodesic distance
- high dimensional data analysis
- head pose estimation
- scatter matrices
- data points
- discriminant analysis