Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size.
Soufiane AjanaNiyazi AcarLionel BretillonBoris P. HejblumHélène Jacqmin-GaddaCécile DelcourtPublished in: Bioinform. (2019)
Keyphrases
- dimension reduction
- high dimensional
- sample size
- high dimensional data
- data sets
- dimensionality reduction
- low dimensional
- small sample size
- data points
- variable selection
- high dimensionality
- model selection
- feature extraction
- linear discriminant analysis
- labeled data
- principal component analysis
- worst case
- knowledge discovery
- input data
- least squares
- linear regression
- regression methods
- data analysis
- high dimensional problems