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Leaderboard and result reports
Sylvain Chevallier edited this page Jan 5, 2023
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Report for the evaluation of pipelines on MOABB datasets
Data filtered between 7-35 Hz. Epoch length are dataset-dependent and use maximum window length.
Dataset | Evaluation type | Pipeline | Average score across subjects | Sessions above chance level |
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Zhou 2016 | WithinSession | CSP + LDA | 0.931489 | |
MDM | 0.907018 | |||
CSP + SVM | 0.932315 | |||
Log Variance LDA | 0.883861 | |||
Tangent Space LR | 0.941601 | |||
Log Variance SVM | 0.854676 | |||
Tangent Space SVM | 0.938613 | |||
CSP + optSVM | 0.928818 | |||
001-2014 | WithinSession | CSP + LDA | 0.823360 | |
MDM | 0.816943 | |||
CSP + SVM | 0.828946 | |||
Log Variance LDA | 0.779562 | |||
Tangent Space LR | 0.874123 | |||
Log Variance SVM | 0.711478 | |||
Tangent Space SVM | 0.864214 | |||
CSP + optSVM | 0.820544 | |||
004-2014 | WithinSession | CSP + LDA | 0.800957 | |
MDM | 0.776555 | |||
CSP + SVM | 0.796910 | |||
Log Variance LDA | 0.785073 | |||
Tangent Space LR | 0.800938 | |||
Log Variance SVM | 0.779423 | |||
Tangent Space SVM | 0.798726 | |||
CSP + optSVM | 0.791219 | |||
Cho2017 | WithinSession | CSP + LDA | 0.711742 | |
MDM | 0.635015 | |||
CSP + SVM | 0.712101 | |||
Log Variance LDA | 0.645397 | |||
Tangent Space LR | 0.745154 | |||
Log Variance SVM | 0.661121 | |||
Tangent Space SVM | 0.743365 | |||
CSP + optSVM | 0.706311 | |||
Physionet Motor Imagery | WithinSession | CSP + LDA | 0.657480 | |
MDM | 0.547599 | |||
CSP + SVM | 0.651111 | |||
Log Variance LDA | 0.619386 | |||
Tangent Space LR | 0.672834 | |||
Log Variance SVM | 0.624919 | |||
Tangent Space SVM | 0.694299 | |||
CSP + optSVM | 0.648555 | |||
Weibo 2014 | WithinSession | CSP + LDA | 0.807191 | |
MDM | 0.588015 | |||
CSP + SVM | 0.801518 | |||
Log Variance LDA | 0.741323 | |||
Tangent Space LR | 0.836191 | |||
Log Variance SVM | 0.728597 | |||
Tangent Space SVM | 0.837777 | |||
CSP + optSVM | 0.798406 | |||
Lee2019_MI | WithinSession | CSP + LDA | 0.768815 | |
MDM | 0.702296 | |||
CSP + SVM | 0.769074 | |||
Log Variance LDA | 0.662278 | |||
Tangent Space LR | 0.830926 | |||
Log Variance SVM | 0.740407 | |||
Tangent Space SVM | 0.841815 | |||
CSP + optSVM | 0.765315 | |||
Grosse-Wentrup 2009 | WithinSession | CSP + LDA | 0.764378 | |
MDM | 0.642911 | |||
CSP + SVM | 0.771578 | |||
Log Variance LDA | 0.787111 | |||
Tangent Space LR | 0.876000 | |||
Log Variance SVM | 0.809867 | |||
Tangent Space SVM | 0.884600 | |||
CSP + optSVM | 0.775644 | |||
Shin2017A | WithinSession | CSP + LDA | 0.722989 | |
MDM | 0.629885 | |||
CSP + SVM | 0.713218 | |||
Log Variance LDA | 0.617816 | |||
Tangent Space LR | 0.693103 | |||
Log Variance SVM | 0.615517 | |||
Tangent Space SVM | 0.721839 | |||
CSP + optSVM | 0.729310 | |||
Schirrmeister2017 | WithinSession | CSP + LDA | 0.772348 | |
MDM | 0.615261 | |||
CSP + SVM | 0.771553 | |||
Log Variance LDA | 0.784386 | |||
Tangent Space LR | 0.872200 | |||
Log Variance SVM | 0.787537 | |||
Tangent Space SVM | 0.876428 | |||
CSP + optSVM | 0.769153 |
Dataset | Pipeline | Evaluation type | Average score across subjects | Sessions above chance level |
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Dataset | Pipeline | Evaluation type | #Classes | Average score across subjects | Sessions above chance level |
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