BCI classification on Lee 2019 (inter-session)
0.682Balanced AccuracyTSMNet(SPDDSMBN)
Evaluation Results
| Method | Links | |
|---|---|---|
| TSMNet(SPDDSMBN)UDA=yes, degrees of freedom=107, classes=22022.06 | 0.682 | |
| FBCSP+DSS+LDAUDA=yes, degrees of freedom=107, classes=22022.06 | 0.668 | |
| SPDOT+TSM+SVMUDA=yes, degrees of freedom=107, classes=22022.06 | 0.656 | |
| FB+TSM+LRUDA=no, degrees of freedom=107, classes=22022.06 | 0.652 | |
| URPA+MDMUDA=yes, degrees of freedom=107, classes=22022.06 | 0.638 | |
| FBCSP+SVMUDA=no, degrees of freedom=107, classes=22022.06 | 0.631 | |
| TSM+SVMUDA=no, degrees of freedom=107, classes=22022.06 | 0.625 | |
| ShConvNet+DANNUDA=yes, degrees of freedom=107, classes=22022.06 | 0.591 | |
| ShConvNetUDA=no, degrees of freedom=107, classes=22022.06 | 0.578 | |
| EEGNet+DANNUDA=yes, degrees of freedom=107, classes=22022.06 | 0.554 | |
| EEGNetUDA=no, degrees of freedom=107, classes=22022.06 | 0.512 |