Visualization of High-Dimensional Data by Pairwise Fusion Matrices Using t-SNE.
Mujtaba HusnainMalik Muhammad Saad MissenShahzad MumtazMuhammad Muzzamil LuqmanMickaël CoustatyJean-Marc OgierPublished in: Symmetry (2019)
Keyphrases
- high dimensional data
- pairwise
- data analysis
- original data
- high dimensional
- dimensionality reduction
- low dimensional
- high dimensionality
- nearest neighbor
- similarity search
- subspace clustering
- data sets
- data points
- high dimensions
- dimension reduction
- input space
- low rank
- linear discriminant analysis
- missing values
- similarity measure
- gene expression data
- sparse representation
- high dimensional datasets
- nonlinear dimensionality reduction
- lower dimensional
- high dimensional spaces
- manifold learning
- subspace learning
- point sets
- high dimensional data sets
- input data
- real world
- dimensional data
- variable weighting
- database
- clustering high dimensional data
- feature extraction
- training set
- spectral clustering
- semi supervised
- principal component analysis
- singular value decomposition