Network-based dimensionality reduction of high-dimensional, low-sample-size datasets.
Zsolt Tibor KosztyánMarcell T. KurbuczAttila Imre KatonaPublished in: Knowl. Based Syst. (2022)
Keyphrases
- sample size
- dimensionality reduction
- high dimensional
- small sample size
- dimensionality reduction methods
- low dimensional
- high dimensionality
- high dimensional data
- statistical tests
- small sample
- random sampling
- model selection
- upper bound
- linear discriminant analysis
- covariance matrix
- feature space
- data points
- pac learning
- experimental design
- principal component analysis
- manifold learning
- input space
- progressive sampling
- principal components
- worst case
- confidence intervals
- vc dimension
- variance reduction
- variable selection
- high dimensional spaces
- data sets
- small samples
- feature selection
- feature extraction
- dimensional data
- objective function
- pattern recognition
- nearest neighbor
- dimension reduction
- gene expression data
- support vector
- training samples
- learning algorithm
- statistical power
- discriminant analysis