Mixtures of common t-factor analyzers for modeling high-dimensional data with missing values.
Wan-Lun WangPublished in: Comput. Stat. Data Anal. (2015)
Keyphrases
- high dimensional data
- missing values
- factor analyzers
- low dimensional
- high dimensional
- dimensionality reduction
- dimension reduction
- manifold learning
- high dimensionality
- incomplete data
- subspace clustering
- data points
- nearest neighbor
- data sets
- original data
- similarity search
- data imputation
- linear discriminant analysis
- high dimensional spaces
- data analysis
- missing data
- sparse representation
- data mining
- low rank
- feature space
- knn
- neural network
- random projections
- clustering high dimensional data
- linear combination
- database