Parameter-wise co-clustering for high-dimensional data.
Michael P. B. GallaugherChristophe BiernackiPaul D. McNicholasPublished in: Comput. Stat. (2023)
Keyphrases
- high dimensional data
- high dimensional datasets
- low dimensional
- high dimensional
- nearest neighbor
- dimensionality reduction
- high dimensionality
- subspace clustering
- data analysis
- high dimensions
- data sets
- data points
- similarity search
- dimension reduction
- clustering algorithm
- input space
- clustering high dimensional data
- missing values
- sparse representation
- original data
- input data
- high dimensional spaces
- lower dimensional
- low rank
- complex data
- linear discriminant analysis
- nonlinear dimensionality reduction
- manifold learning
- clustering method
- dimensional data
- image data
- data distribution
- text data
- neural network
- machine learning
- database
- pattern recognition
- feature space
- semi supervised
- principal component analysis