<p>Ranking of different algorithms with respect to the median AUC in a 10 times repeated 10-fold cross-validation procedure.</p
<p>Comparison of kernelPLS with four other methods. For 10-fold cross validation classification accu...
<p>General method ranking, obtained by sorting methods according to their average ranking across 6 d...
<p>Ranking of each method, as determined by statistical analysis, by individual sample type and comb...
<p>Ranks of All Classification Methods Used in This Study in Ten Cross-Validation Experiments</p
<p>Rankings of the algorithms by the Friedman’s test on the basic benchmark functions.</p
<p>Comparison of the average classification accuracies of different algorithms for different numbers...
<p>Rankings of the algorithms by the Friedman’s test on the CEC2005’s shifted functions.</p
<p>The number in the parenthesis corresponds to the average rank of the algorithm among different su...
<p>The number of subjects in binary task was 12 and the number of subjects in multi-task BCIs was 9....
This chapter first introduces the main issues of multi-criteria decision analysis (MCDA). This invol...
<p>Individual coverage probability with a maximum difference of 0.1 m/s (CP1) to 0.3 m/s (CP3) as we...
<p>(a) The candidate features are ranked by AUC scores calculated on hg19 Training-A; (b) The candid...
<p>Individual coverage probability with a maximum difference of 0.1 m/s (CP1) to 0.3 m/s (CP3) as we...
<p>Each data point is obtained by averaging over ten runs, each of which has an independently random...
<p>“*”: Geometric mean (GM); Stability Value (SV); Pearson's correlation coefficient ([r]); Standard...
<p>Comparison of kernelPLS with four other methods. For 10-fold cross validation classification accu...
<p>General method ranking, obtained by sorting methods according to their average ranking across 6 d...
<p>Ranking of each method, as determined by statistical analysis, by individual sample type and comb...
<p>Ranks of All Classification Methods Used in This Study in Ten Cross-Validation Experiments</p
<p>Rankings of the algorithms by the Friedman’s test on the basic benchmark functions.</p
<p>Comparison of the average classification accuracies of different algorithms for different numbers...
<p>Rankings of the algorithms by the Friedman’s test on the CEC2005’s shifted functions.</p
<p>The number in the parenthesis corresponds to the average rank of the algorithm among different su...
<p>The number of subjects in binary task was 12 and the number of subjects in multi-task BCIs was 9....
This chapter first introduces the main issues of multi-criteria decision analysis (MCDA). This invol...
<p>Individual coverage probability with a maximum difference of 0.1 m/s (CP1) to 0.3 m/s (CP3) as we...
<p>(a) The candidate features are ranked by AUC scores calculated on hg19 Training-A; (b) The candid...
<p>Individual coverage probability with a maximum difference of 0.1 m/s (CP1) to 0.3 m/s (CP3) as we...
<p>Each data point is obtained by averaging over ten runs, each of which has an independently random...
<p>“*”: Geometric mean (GM); Stability Value (SV); Pearson's correlation coefficient ([r]); Standard...
<p>Comparison of kernelPLS with four other methods. For 10-fold cross validation classification accu...
<p>General method ranking, obtained by sorting methods according to their average ranking across 6 d...
<p>Ranking of each method, as determined by statistical analysis, by individual sample type and comb...