A Geometry-Based Approach to Visualize High-Dimensional Data.
Caio FlexaWalisson Cardoso GomesSérgio ViademonteClaudomiro Souza JuniorRonnie AlvesPublished in: BRACIS (2019)
Keyphrases
- high dimensional data
- dimensionality reduction
- nearest neighbor
- high dimensionality
- high dimensional
- data sets
- low dimensional
- data points
- subspace clustering
- high dimensions
- data analysis
- low dimensional manifolds
- similarity search
- original data
- dimension reduction
- input space
- nonlinear dimensionality reduction
- high dimensional datasets
- sparse representation
- underlying manifold
- data distribution
- clustering high dimensional data
- subspace learning
- lower dimensional
- manifold learning
- input data
- computer vision
- dimensional data
- principal component analysis
- image data
- high dimensional data sets
- machine learning
- data mining