An adaptive accuracy-weighted ensemble for inter-subjects classification in brain-computer interfacing.
Sami DalhoumiGérard DrayJacky MontmainGérard DerosièreStéphane PerreyPublished in: NER (2015)
Keyphrases
- classification accuracy
- accuracy rate
- fold cross validation
- normal controls
- final classification
- individual classifiers
- training set
- eeg data
- ensemble classifier
- eeg signals
- combination of multiple classifiers
- healthy controls
- machine learning
- support vector
- feature selection
- decision trees
- training data
- ensemble learning
- feature space
- feature vectors
- classifier ensemble
- computer screen
- classifier combination
- supervised learning
- support vector machine svm
- classification rate
- machine learning methods
- pattern classification
- generalization ability
- class labels
- brain signals
- svm classifier
- feature extraction
- publicly available data sets
- decision tree classifiers
- regression problems
- multiple classifiers
- naive bayes
- functional magnetic resonance imaging
- k nearest neighbour
- prediction accuracy
- intra class