Matrix correlations for high-dimensional data: the modified RV-coefficient.
Age K. SmildeHenk A. L. KiersS. BijlsmaC. M. RubinghM. J. van ErkPublished in: Bioinform. (2009)
Keyphrases
- high dimensional data
- low rank
- low dimensional
- dimensionality reduction
- high dimensional
- nearest neighbor
- high dimensionality
- high dimensions
- data sets
- data points
- data analysis
- subspace clustering
- similarity search
- dimension reduction
- original data
- dimensional data
- missing values
- clustering high dimensional data
- data distribution
- singular value decomposition
- high dimensional spaces
- linear discriminant analysis
- lower dimensional
- pairwise
- manifold learning
- input space
- text data
- kernel matrix
- feature selection
- high dimensional datasets
- neural network
- small sample size
- machine learning
- locally linear embedding
- computer vision
- support vector
- pattern recognition
- sparse representation