Multi-class f-score feature selection approach to classification of obstructive sleep apnea syndrome.
Salih GünesKemal PolatSebnem YosunkayaPublished in: Expert Syst. Appl. (2010)
Keyphrases
- multi class
- feature selection
- obstructive sleep apnea
- support vector machine
- multiclass classification
- multi class classification
- multi class classifier
- binary and multi class
- binary classifiers
- multiple classes
- cost sensitive
- classification accuracy
- multi class boosting
- multiclass problems
- binary classification problems
- binary classification
- multi class svms
- eeg signals
- multi class svm
- text classification
- binary classification tasks
- support vector
- feature set
- feature space
- feature extraction
- error correcting output codes
- high dimensionality
- machine learning
- svm classifier
- support vector machine svm
- sleep apnea
- single class
- pattern recognition
- machine learning methods
- probabilistic boosting tree
- protein classification
- multi task
- multi class problems
- class imbalance
- text categorization
- training data
- radial basis function neural network
- class distribution
- generalization ability
- pattern classification
- k nearest neighbor
- model selection
- decision trees
- learning algorithm