Investigation of Efficiency and Accuracy of Deep Learning Models and Features with Electroencephalogram (EEG) Data for Binary Classification.
Kelly O'BrienLiam BrownJoaquim GonçalvesPublished in: ISDFS (2024)
Keyphrases
- learning models
- binary classification
- learning problems
- eeg data
- eeg signals
- prediction accuracy
- classification models
- learning tasks
- multi class
- machine learning
- learning algorithm
- classification accuracy
- brain computer interface
- semi supervised learning
- support vector
- prior knowledge
- supervised learning
- cost sensitive
- conditional random fields
- loss function
- multi label
- generalization error
- extracted features
- feature extraction
- data sets
- support vector machine
- machine learning algorithms
- bayesian networks
- class imbalance
- feature set
- image features
- brain activity