Self Organized Swarms for cluster preserving Projections of high-dimensional Data.
Alfred UltschLutz HerrmannPublished in: Electron. Commun. Eur. Assoc. Softw. Sci. Technol. (2010)
Keyphrases
- high dimensional data
- subspace clustering
- data points
- low dimensional
- high dimensional
- nearest neighbor
- dimensionality reduction
- variable weighting
- high dimensionality
- high dimensions
- data analysis
- cluster structure
- data sets
- similarity search
- clustering algorithm
- clustering high dimensional data
- dimension reduction
- input space
- data clustering
- lower dimensional
- particle swarm optimization
- linear discriminant analysis
- original data
- dimensional data
- high dimensional datasets
- output space
- high dimensional spaces
- gene expression data
- small sample size
- subspace clusters
- subspace learning
- text data
- manifold learning
- data distribution
- sparse representation
- input data
- feature space
- cluster analysis
- nonlinear dimensionality reduction
- high dimensional data sets
- pattern recognition
- data structure
- feature selection