Accelerating Density-Based Subspace Clustering in High-Dimensional Data.
Jürgen PrinzbachTobias LauerNicolas KieferPublished in: ICDM (Workshops) (2021)
Keyphrases
- subspace clustering
- high dimensional data
- dimensionality reduction
- nearest neighbor
- low dimensional
- high dimensional
- data analysis
- data sets
- original data
- high dimensionality
- subspace clusters
- clustering high dimensional data
- data points
- data distribution
- similarity search
- dimension reduction
- high dimensional datasets
- linear discriminant analysis
- high dimensional feature spaces
- manifold learning
- clustering method
- complex data
- input space
- text data
- computer vision
- lower dimensional
- face recognition
- high dimensional spaces
- dense regions
- subspace projections
- subspace clustering algorithms
- small sample size
- dimensional data
- subspace learning
- principal component analysis
- similarity measure
- real world