Using the left Gram matrix to cluster high dimensional data.
Shahina RahmanValen E. JohnsonSuhasini Subba RaoPublished in: CoRR (2022)
Keyphrases
- high dimensional data
- gram matrix
- subspace clustering
- data points
- dimensionality reduction
- nearest neighbor
- low dimensional
- high dimensional
- cluster structure
- data sets
- high dimensionality
- rows and columns
- data analysis
- original data
- kernel pca
- similarity search
- sparse representation
- positive definite
- dimensional data
- dimension reduction
- kernel function
- input space
- low rank
- linear discriminant analysis
- missing values
- manifold learning
- clustering algorithm
- nonlinear dimensionality reduction
- gene expression data
- principal component analysis
- input data
- regression problems
- cluster analysis
- euclidean space
- knn
- cluster centers
- subspace learning
- discriminant analysis
- euclidean distance
- training data