Multi-class Classification on BrainFlow N=32 Channels (test)
100Test AccuracyRandom Forest (50 Trees)
Evaluation Results
| Method | Links | |
|---|---|---|
| Random Forest (50 Trees)Optimization Class=Ensemble, Trainable Parameters=Non-parametric2026.03 | 100 | |
| Support Vector MachineOptimization Class=RBF Kernels, Trainable Parameters=Non-parametric2026.03 | 100 | |
| Neural Network (MLP)Optimization Class=Adam Descent, Trainable Parameters=2372 Euclidean Floats2026.03 | 100 | |
| PhasorFlow VPC (S1)Optimization Class=PyTorch Adam, Trainable Parameters=64 Continuous Phases2026.03 | 99 | |
| Decision Tree (Depth=5)Optimization Class=Axis Splitting, Trainable Parameters=Non-parametric2026.03 | 96 |