Cepstrum Feature Selection for the Classification of Sleep Apnea-Hypopnea Syndrome based on Heart Rate Variability.
Antonio G. Ravelo-GarcíaJuan L. Navarro-MesaEduardo Hernández-PérezSofía I. Martín-GonzálezPedro J. Quintana-MoralesIván Guerra MorenoGabriel Juliá-SerdáPublished in: CinC (2013)
Keyphrases
- sleep stage
- feature selection
- apnea hypopnea
- sleep apnea
- obstructive sleep apnea
- heart rate variability
- support vector
- classification accuracy
- machine learning
- feature space
- text classification
- decision trees
- high dimensionality
- feature reduction
- spectral analysis
- feature selection algorithms
- feature extraction
- text categorization
- image classification
- feature set
- selected features
- physiological parameters
- support vector machine
- feature vectors
- pattern recognition
- decision rules
- feature subset
- classification models
- heart rate
- feature ranking
- dimensionality reduction
- training data