Comparing and Exploring High-Dimensional Data with Dimensionality Reduction Algorithms and Matrix Visualizations.
René CuturaMichaël AupetitJean-Daniel FeketeMichael SedlmairPublished in: AVI (2020)
Keyphrases
- high dimensional data
- dimensionality reduction
- low dimensional
- high dimensional
- high dimensionality
- high dimensional spaces
- low rank
- data sets
- dimensional data
- nearest neighbor
- high dimensional datasets
- data points
- singular value decomposition
- high dimensions
- nonlinear dimensionality reduction
- principal component analysis
- manifold learning
- subspace clustering
- high dimensional data sets
- missing values
- original data
- linear discriminant analysis
- input space
- dimensionality reduction methods
- sparse representation
- dimension reduction
- pattern recognition
- locally linear embedding
- feature space
- data analysis
- subspace learning
- feature extraction
- feature selection
- computer vision
- learning algorithm
- knn
- data structure