A latent variables approach for clustering mixed binary and continuous variables within a Gaussian mixture model.
Isabella MorliniPublished in: Adv. Data Anal. Classif. (2012)
Keyphrases
- gaussian mixture model
- latent variables
- continuous variables
- random variables
- hidden variables
- probabilistic model
- mixture model
- em algorithm
- posterior distribution
- clustering algorithm
- expectation maximization
- bayesian networks
- prior knowledge
- feature vectors
- topic models
- graphical models
- approximate inference
- feature space
- gaussian distribution
- structure learning
- generative model
- unsupervised learning
- gaussian process
- k means
- dynamic systems
- maximum likelihood
- probability distribution
- structured prediction
- posterior probability
- learning algorithm
- markov networks
- high dimensional data
- language model