Optimal Clustering and Cluster Identity in Understanding High-Dimensional Data Spaces with Tightly Distributed Points.
Oliver ChikumboVincent GranvillePublished in: Mach. Learn. Knowl. Extr. (2019)
Keyphrases
- high dimensional data
- data points
- subspace clustering
- high dimensionality
- cluster structure
- dimensionality reduction
- high dimensional
- nearest neighbor
- cluster centers
- low dimensional
- clustering algorithm
- high dimensions
- data sets
- similarity search
- hyperplane
- input space
- data distribution
- high dimensional data sets
- variable weighting
- dimension reduction
- lower dimensional
- nonlinear dimensionality reduction
- data clustering
- feature space
- linear discriminant analysis
- subspace clustering algorithms
- original data
- data analysis
- clustering high dimensional data
- input data
- high dimensional spaces
- euclidean space
- high dimensional datasets
- distance function
- hierarchical clustering
- dimensional data
- point sets
- subspace clusters
- manifold learning
- spectral clustering
- text data
- euclidean distance
- latent space
- clustering method
- query processing
- gene expression data