Simultaneous high-dimensional clustering and feature selection using asymmetric Gaussian mixture models.
Tarek ElguebalyNizar BouguilaPublished in: Image Vis. Comput. (2015)
Keyphrases
- gaussian mixture model
- high dimensional
- high dimensionality
- feature space
- feature selection
- finite mixture models
- mixture model
- data points
- dimensionality reduction
- high dimensional data
- bayesian information criterion
- density estimation
- feature vectors
- unsupervised learning
- k means
- em algorithm
- expectation maximization
- microarray data
- low dimensional
- speaker recognition
- similarity search
- clustering algorithm
- probability density
- maximum likelihood
- gaussian mixture
- gene expression data
- classification accuracy
- feature extraction
- model based clustering
- variational bayes
- finite mixtures
- model selection
- feature set
- nearest neighbor
- face recognition
- machine learning
- self organizing maps
- text data
- data sets
- covariance matrices
- speaker identification
- support vector
- decision trees
- minimum message length
- learning algorithm