Simultaneous dimension reduction and variable selection in modeling high dimensional data.
Joseph Ryan G. LansanganErniel B. BarriosPublished in: Comput. Stat. Data Anal. (2017)
Keyphrases
- dimension reduction
- variable selection
- high dimensional data
- high dimensional
- low dimensional
- high dimensionality
- dimensionality reduction
- nearest neighbor
- data analysis
- manifold learning
- high dimensions
- data sets
- linear discriminant analysis
- high dimensional data analysis
- subspace clustering
- data points
- random projections
- principal component analysis
- lower dimensional
- similarity search
- original data
- high dimensional spaces
- intrinsic dimension
- input space
- low rank
- variable weighting
- singular value decomposition
- feature extraction
- ls svm
- cluster analysis
- model selection
- locally linear embedding
- maximum likelihood
- pairwise
- preprocessing