Classification of high-dimensional data with spiked covariance matrix structure.
Yin-Jen ChenMinh TangPublished in: CoRR (2021)
Keyphrases
- high dimensional data
- covariance matrix
- high dimensionality
- dimensionality reduction
- dimension reduction
- small sample size
- sample size
- principal component analysis
- low dimensional
- class conditional densities
- covariance matrices
- high dimensional
- nearest neighbor
- principal components analysis
- linear discriminant analysis
- clustering high dimensional data
- underlying manifold
- feature space
- data sets
- multivariate temporal data
- pattern recognition
- manifold learning
- gaussian mixture
- subspace clustering
- similarity search
- data points
- data distribution
- machine learning
- feature selection
- feature extraction
- data analysis
- decision trees
- feature vectors
- sparse representation
- genetic algorithm
- high dimensional spaces
- low rank
- locally linear embedding
- training set
- support vector machine
- model selection
- support vector machine svm