Depuration, augmentation and balancing of training data for supervised learning based detectors of EEG patterns.
Daniel Lachner PizaAndreas Schulze-BonhageThomas StieglitzJulia JacobsMatthias DümpelmannPublished in: NER (2017)
Keyphrases
- supervised learning
- training data
- training patterns
- learning algorithm
- training set
- training examples
- learning problems
- learning tasks
- unsupervised learning
- class labels
- training samples
- semi supervised
- decision trees
- labeled data
- generalization error
- event related potentials
- unlabeled data
- semi supervised learning
- prior knowledge
- classification accuracy
- data sets
- reinforcement learning
- test data
- active learning
- pattern discovery
- classification models
- machine learning
- domain knowledge
- pattern mining
- test set
- brain computer interface
- training dataset
- training instances
- event related
- neural network
- learned from training data