Cluster-weighted t-factor analyzers for robust model-based clustering and dimension reduction.
Sanjeena SubediAntonio PunzoSalvatore IngrassiaPaul D. McNicholasPublished in: Stat. Methods Appl. (2015)
Keyphrases
- dimension reduction
- model based clustering
- low dimensional
- hierarchical clustering
- cluster analysis
- factor analyzers
- principal component analysis
- mixture model
- feature extraction
- high dimensional
- singular value decomposition
- clustering algorithm
- agglomerative hierarchical clustering
- em algorithm
- variable selection
- k means
- expectation maximization
- feature space
- feature selection
- dimensionality reduction
- bayesian information criterion
- unsupervised learning
- high dimensional data
- data points
- linear discriminant analysis
- high dimensionality
- preprocessing
- machine learning
- data analysis
- object recognition
- information retrieval