Modelling high-dimensional data by mixtures of factor analyzers.
Geoffrey J. McLachlanDavid PeelRichard W. BeanPublished in: Comput. Stat. Data Anal. (2003)
Keyphrases
- factor analyzers
- high dimensional data
- low dimensional
- high dimensional
- dimensionality reduction
- high dimensionality
- data points
- subspace clustering
- manifold learning
- original data
- principal component analysis
- input space
- similarity search
- high dimensions
- dimension reduction
- lower dimensional
- nearest neighbor
- feature space
- data analysis
- subspace learning
- linear discriminant analysis
- complex data
- clustering high dimensional data
- data sets
- nonlinear dimensionality reduction
- data distribution
- high dimensional spaces
- variable selection
- dimensional data
- sparse representation
- decision trees
- text data
- small sample size
- real world