<p>The number of subjects in binary task was 12 and the number of subjects in multi-task BCIs was 9. The number in the parenthesis corresponds to the average rank of the algorithm among different subjects. For each feature extraction method the classifiers typed in bold are the recommended ones. The recommended classifiers are selected based on the results of the statistical tests.</p
Comparison of the average classification accuracies of the proposed algorithm for different numbers ...
This data provides the detailed test results of the benchmarking for the binary-classification perfo...
All artificial datasets were used for evaluation. The averages were calculated separately for datase...
<p>The number in the parenthesis corresponds to the average rank of the algorithm among different su...
<p>Comparison of the average classification accuracies of different algorithms for different numbers...
<p>Each algorithm trained using selected features and evaluated with 10-fold cross-validation. Value...
<p>The average ranks of the Friedman test for the seven different classifiers using the additive enc...
<p>Ranking of different algorithms with respect to the median AUC in a 10 times repeated 10-fold cro...
The aim of this paper is to discuss about various feature selection algorithms applied on different ...
<p>Comparison of the recognition rates of the proposed method with some popular classifiers in the l...
This research uses four classification algorithms in standard and boosted forms to predict members o...
<p>The performances of the different classification algorithms as a function of the number of trials...
Microsoft, Motorola, Siemens, Hitachi, IAPR, NICI, IUF The Borda count is a simple yet effective met...
<p>Performance for all classification algorithms over all peak picking and peak clustering algorithm...
<p>Comparison of the average precision rates, recall rates and F1 values for the different classific...
Comparison of the average classification accuracies of the proposed algorithm for different numbers ...
This data provides the detailed test results of the benchmarking for the binary-classification perfo...
All artificial datasets were used for evaluation. The averages were calculated separately for datase...
<p>The number in the parenthesis corresponds to the average rank of the algorithm among different su...
<p>Comparison of the average classification accuracies of different algorithms for different numbers...
<p>Each algorithm trained using selected features and evaluated with 10-fold cross-validation. Value...
<p>The average ranks of the Friedman test for the seven different classifiers using the additive enc...
<p>Ranking of different algorithms with respect to the median AUC in a 10 times repeated 10-fold cro...
The aim of this paper is to discuss about various feature selection algorithms applied on different ...
<p>Comparison of the recognition rates of the proposed method with some popular classifiers in the l...
This research uses four classification algorithms in standard and boosted forms to predict members o...
<p>The performances of the different classification algorithms as a function of the number of trials...
Microsoft, Motorola, Siemens, Hitachi, IAPR, NICI, IUF The Borda count is a simple yet effective met...
<p>Performance for all classification algorithms over all peak picking and peak clustering algorithm...
<p>Comparison of the average precision rates, recall rates and F1 values for the different classific...
Comparison of the average classification accuracies of the proposed algorithm for different numbers ...
This data provides the detailed test results of the benchmarking for the binary-classification perfo...
All artificial datasets were used for evaluation. The averages were calculated separately for datase...