A Contribution for the Automatic Sleep Classification Based on the Itakura-Saito Spectral Distance.
Eduardo CardosoArnaldo BatistaRui RodriguesManuel Duarte OrtigueiraCristina BárbaraCristina MartinhoRaul Tello RatoPublished in: DoCEIS (2010)
Keyphrases
- pattern recognition
- sleep stage
- classification accuracy
- decision trees
- spectral features
- feature extraction
- feature vectors
- machine learning
- statistical classification
- relative entropy
- bregman divergences
- classification scheme
- support vector machine svm
- support vector machine
- mixture model
- feature selection
- distance measure
- mahalanobis distance
- image classification
- cost sensitive
- classification algorithm
- semi automatic
- euclidean distance
- class labels
- training samples
- eeg signals
- maximum likelihood
- training set
- model selection
- neural network