EEG Hemisphere Classification on Necker Cube
16Negative CountReal-Time Neurofeedback Decision Algorithm
Evaluation Results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| Real-Time Neurofeedback Decision AlgorithmCategory=Dataset2025.09 | 16 | 1 | 3 | 20 | 44.7 | |
| Random ForestCategory=Model Type, Scope=Aggregate2025.09 | 10 | 0 | 0 | 10 | 0 | |
| SVM (RBF)Category=Model Type, Scope=Aggregate2025.09 | 10 | 0 | 0 | 10 | 0 | |
| Real-Time Neurofeedback Decision AlgorithmBrain Rhythm=δ, Scope=Aggregate2025.09 | 8 | 0 | 0 | 8 | 0 | |
| Real-Time Neurofeedback Decision AlgorithmBrain Rhythm=θ, Scope=Aggregate2025.09 | 8 | 0 | 0 | 8 | 0 | |
| SVM (Linear)Category=Model Type, Scope=Aggregate2025.09 | 7 | 3 | 0 | 10 | 0 | |
| Real-Time Neurofeedback Decision AlgorithmBrain Rhythm=α, Scope=Aggregate2025.09 | 7 | 0 | 1 | 8 | 42.6 | |
| Deep Neural Network (RMSprop)Category=Model Type, Scope=Aggregate2025.09 | 5 | 0 | 5 | 10 | 44.7 | |
| Real-Time Neurofeedback Decision AlgorithmBrain Rhythm=γ, Scope=Aggregate2025.09 | 5 | 1 | 2 | 8 | 29.8 | |
| Real-Time Neurofeedback Decision AlgorithmBrain Rhythm=β, Scope=Aggregate2025.09 | 4 | 2 | 2 | 8 | 44.7 |