<p>PCHIP and moving average features classify better than conventional parameters, and slightly better than all nonzero initial conditions.</p
<p>Classification accuracies for each identity (mean in %) and average accuracies (mean and standard...
Comparison of classification accuracies of dataset 2 with different classifiers.</p
First scenario classification accuracies under different feature subsets and classifiers.</p
<p>Best classification accuracies and number of features to produce accuracies.</p
<p>Classification accuracies(%) of the subjects under the two different conditions.</p
<p>Classification accuracies (%) comparison on Dataset IVa of BCI Competition III.</p
<p>*statistically significantly better (p<0.05, t-test) as compared to the results with the original...
<p>Overall accuracies (%), kappa coefficients and classification speed using various classifiers bas...
<p>The classification accuracy for various feature subsets, averaged over all the class definitions....
Comparison of classification accuracies of dataset 1 with different classifiers.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
Predictive accuracies of classifiers against benchmark datasets with varying percentages of retained...
<p>Classification accuracy (%) for all subjects using different feature extraction methods.</p
Comparison of the classification accuracies of different algorithms and different feature fusion met...
<p>Classification accuracies without data correction or stratification (original) and the best accur...
<p>Classification accuracies for each identity (mean in %) and average accuracies (mean and standard...
Comparison of classification accuracies of dataset 2 with different classifiers.</p
First scenario classification accuracies under different feature subsets and classifiers.</p
<p>Best classification accuracies and number of features to produce accuracies.</p
<p>Classification accuracies(%) of the subjects under the two different conditions.</p
<p>Classification accuracies (%) comparison on Dataset IVa of BCI Competition III.</p
<p>*statistically significantly better (p<0.05, t-test) as compared to the results with the original...
<p>Overall accuracies (%), kappa coefficients and classification speed using various classifiers bas...
<p>The classification accuracy for various feature subsets, averaged over all the class definitions....
Comparison of classification accuracies of dataset 1 with different classifiers.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
Predictive accuracies of classifiers against benchmark datasets with varying percentages of retained...
<p>Classification accuracy (%) for all subjects using different feature extraction methods.</p
Comparison of the classification accuracies of different algorithms and different feature fusion met...
<p>Classification accuracies without data correction or stratification (original) and the best accur...
<p>Classification accuracies for each identity (mean in %) and average accuracies (mean and standard...
Comparison of classification accuracies of dataset 2 with different classifiers.</p
First scenario classification accuracies under different feature subsets and classifiers.</p
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