Finding Well-Clusterable Subspaces for High Dimensional Data - A Numerical One-Dimension Approach.
Chuanren LiuTianming HuYong GeHui XiongPublished in: PAKDD (2) (2014)
Keyphrases
- high dimensional data
- low dimensional
- dimensional data
- high dimensional
- dimensionality reduction
- high dimensions
- subspace clustering
- high dimensionality
- nearest neighbor
- data sets
- high dimension
- data points
- similarity search
- intrinsic dimension
- original data
- data distribution
- linear discriminant analysis
- lower dimensional
- data analysis
- input space
- dimension reduction
- low rank
- manifold learning
- text data
- sparse representation
- locally linear embedding
- clustering high dimensional data
- high dimensional spaces
- input data
- computer vision
- subspace learning
- high dimensional datasets
- similarity measure
- small sample size
- high dimensional data sets
- high dimensional feature spaces
- feature extraction