Self-reconstructive evidential clustering for high-dimensional data.
Chaoyu GongYongbin LiuDi FuYong LiuPei-hong WangYang YouPublished in: ICDE (2022)
Keyphrases
- high dimensional data
- high dimensionality
- subspace clustering
- data points
- low dimensional
- dimensionality reduction
- high dimensional
- nearest neighbor
- data sets
- high dimensional data sets
- data analysis
- original data
- dimension reduction
- similarity search
- high dimensions
- high dimensional datasets
- clustering high dimensional data
- input space
- manifold learning
- sparse representation
- dimensional data
- input data
- high dimensional spaces
- sparse coding
- clustering algorithm
- small sample size
- text data
- subspace learning
- high dimensional data analysis
- gene expression data
- linear discriminant analysis
- data distribution
- principal component analysis
- computer vision
- machine learning
- lower dimensional
- locally linear embedding
- training data
- feature extraction
- data mining