Approximated Clustering of Distributed High-Dimensional Data.
Hans-Peter KriegelPeter KunathMartin PfeifleMatthias RenzPublished in: PAKDD (2005)
Keyphrases
- high dimensional data
- subspace clustering
- low dimensional
- data points
- high dimensionality
- nearest neighbor
- high dimensional
- dimensionality reduction
- high dimensions
- data sets
- similarity search
- data analysis
- original data
- clustering high dimensional data
- data distribution
- high dimensional data sets
- input space
- sparse representation
- dimension reduction
- linear discriminant analysis
- high dimensional datasets
- manifold learning
- high dimensional spaces
- lower dimensional
- small sample size
- nonlinear dimensionality reduction
- linear combination
- high dimensional feature spaces
- dimensional data
- pattern recognition
- input data
- principal component analysis
- locally linear embedding
- cluster analysis
- variable weighting
- text data
- distance function
- unsupervised learning
- multi dimensional
- feature space
- real world