Graph-Based Semi-supervised Learning Using Riemannian Geometry Distance for Motor Imagery Classification.
Eric SmrkovskyHubert CecottiPublished in: MCPR (2023)
Keyphrases
- motor imagery
- eeg signals
- graph based semi supervised learning
- brain computer interface
- classification accuracy
- pattern recognition
- geodesic distance
- feature selection
- feature vectors
- text classification
- semi supervised learning
- decision trees
- training set
- distance measure
- data analysis
- feature extraction
- machine learning
- distance function
- pattern classification
- manifold learning
- human brain
- feature space