Simultaneous dimension reduction and clustering via the NMF-EM algorithm.
Léna CarelPierre AlquierPublished in: Adv. Data Anal. Classif. (2021)
Keyphrases
- dimension reduction
- em algorithm
- matrix factorisation
- expectation maximization
- unsupervised learning
- cluster analysis
- probabilistic latent semantic analysis
- principal component analysis
- mixture model
- finite mixture models
- high dimensional data
- high dimensionality
- generative topographic mapping
- nonnegative matrix factorization
- maximum likelihood
- model based clustering
- high dimensional
- mixture modeling
- document clustering
- k means
- feature extraction
- expectation maximisation
- negative matrix factorization
- gaussian mixture model
- generative model
- low dimensional
- singular value decomposition
- gaussian mixture
- density estimation
- variable selection
- feature space
- feature selection
- manifold learning
- data clustering
- clustering method
- dimensionality reduction
- spectral clustering
- probabilistic model
- probability density function
- data sets
- clustering algorithm
- least squares
- self organizing maps
- discriminative information
- hierarchical clustering
- data points
- semi supervised
- image processing