Mixtures of Factor Analyzers with Common Factor Loadings: Applications to the Clustering and Visualization of High-Dimensional Data.
Jangsun BaekGeoffrey J. McLachlanLloyd K. FlackPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2010)
Keyphrases
- high dimensional data
- factor analyzers
- low dimensional
- high dimensional
- high dimensionality
- data points
- data analysis
- dimensionality reduction
- subspace clustering
- high dimensions
- manifold learning
- factor analysis
- nearest neighbor
- principal component analysis
- high dimensional datasets
- input space
- similarity search
- high dimensional data sets
- clustering high dimensional data
- self organizing maps
- data sets
- original data
- dimension reduction
- feature space
- high dimensional spaces
- lower dimensional
- euclidean space
- locally linear embedding
- dimensional data
- linear discriminant analysis
- nonlinear dimensionality reduction
- sparse representation
- small sample size
- learning algorithm
- pattern recognition
- text data
- cluster analysis
- image processing
- input data
- clustering algorithm