Universum based Lagrangian twin bounded support vector machine to classify EEG signals.
Bikram KumarDeepak GuptaPublished in: Comput. Methods Programs Biomed. (2021)
Keyphrases
- eeg signals
- support vector machine
- binary classification
- maximum margin
- unbalanced data
- semi supervised learning
- support vector
- multi class
- signal processing
- svm classifier
- cost sensitive
- brain computer interface
- misclassification costs
- kernel methods
- hyperplane
- training set
- training data
- support vector machine svm
- feature vectors
- k nearest neighbor
- semi definite programming
- machine learning
- feature selection
- eeg data
- kernel function
- decision boundary
- support vectors
- regression method
- generalization error
- structured output
- class distribution
- semi supervised
- labeled data
- learning algorithm
- standard svm
- ls svm
- extracted features
- support vector regression
- pattern classification
- multi label