Incomplete-Data Oriented Dimension Reduction via Instance Factoring PCA Framework.
Ernest Domanaanmwi GanaaTimothy Apasiba AbeoSumet MehtaHeping SongXiang-Jun ShenPublished in: ICIG (3) (2019)
Keyphrases
- dimension reduction
- principal component analysis
- incomplete data
- feature extraction
- high dimensional
- high dimensional data analysis
- dimensionality reduction
- low dimensional
- feature subspace
- high dimensional data
- singular value decomposition
- random projections
- dimension reduction methods
- linear discriminant analysis
- high dimensional problems
- high dimensionality
- discriminant analysis
- learning bayesian networks
- principle component analysis
- sparse metric learning
- missing values
- unsupervised learning
- least squares
- feature space
- bayesian networks
- manifold learning
- independent component analysis
- cluster analysis
- manifold embedding
- machine learning
- data sets