Simultaneous feature selection and Gaussian mixture model estimation for supervised classification problems.
Jens KerstenPublished in: Pattern Recognit. (2014)
Keyphrases
- gaussian mixture model
- feature selection
- feature space
- mixture model
- probability density
- density estimation
- unsupervised learning
- em algorithm
- feature vectors
- expectation maximization
- maximum likelihood
- speaker recognition
- maximum likelihood estimation
- gaussian mixture
- machine learning
- background subtraction
- maximum likelihood criterion
- model selection
- probability density function
- text classification
- support vector
- feature extraction
- dimensionality reduction
- gaussian mixture modeling
- speaker identification
- gaussian model
- selection criterion
- high dimensional
- probabilistic model
- data sets
- decision trees
- computer vision
- face recognition
- mixture distribution
- semi supervised
- supervised learning