Analyzing High-Dimensional Data by Subspace Validity.
Amihood AmirReuven KashiNathan S. NetanyahuDaniel A. KeimMarkus WawryniukPublished in: ICDM (2003)
Keyphrases
- high dimensional data
- subspace clustering
- low dimensional
- dimensionality reduction
- nearest neighbor
- high dimensional
- clustering high dimensional data
- high dimensions
- data sets
- high dimensionality
- data points
- lower dimensional
- dimension reduction
- similarity search
- input space
- data analysis
- sparse representation
- original data
- data distribution
- manifold learning
- high dimensional datasets
- high dimensional spaces
- linear discriminant analysis
- subspace clusters
- high dimensional data sets
- principal component analysis
- subspace learning
- dimensional data
- computer vision
- nonlinear dimensionality reduction
- locally linear embedding
- decision trees
- image processing
- pattern recognition
- learning algorithm
- low rank
- data mining
- input data
- database