<p>10-fold cross-validation of static SSVEP classification by the quantity of training data.</p
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
Cross-validation test results for the context-specific algorithms under study.</p
<p>10% of the data were defined as test dataset (TestData1) while the remaining 90% (TrainingData1) ...
<p>(a) Average of all subjects in static SSVEP. (b) Low performing subjects. 1,500 test data were us...
<p>10-Fold Cross Validation Accuracies of the classifiers applied to the Artificial dataset.</p
<p>The prediction results compared with other methods on the training dataset using 10-fold cross-va...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Results for different basic classifiers (mean±SD) by using varied numbers of supplementary traini...
<p>The data set is partitioned into 10 parts (folds) in the outer loop. One fold of the data set is ...
Performance of different modules on training sets using 5-fold cross-validation.</p
<p>10-Fold Cross Validation Accuracy of classification methods with the addition of noisy variables....
<p>Classification rates using ten-fold cross-validation (10-fold) versus using only the 1<sup>st</su...
<p>Evaluation of regression algorithms on 10-fold cross-validation on the SICK training corpus.</p
Background: The bootstrap can be alternative to cross-validation as a training/test set splitting me...
<p>The number of misclassified samples for each run and the final accuracy using 10-fold cross-valid...
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
Cross-validation test results for the context-specific algorithms under study.</p
<p>10% of the data were defined as test dataset (TestData1) while the remaining 90% (TrainingData1) ...
<p>(a) Average of all subjects in static SSVEP. (b) Low performing subjects. 1,500 test data were us...
<p>10-Fold Cross Validation Accuracies of the classifiers applied to the Artificial dataset.</p
<p>The prediction results compared with other methods on the training dataset using 10-fold cross-va...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Results for different basic classifiers (mean±SD) by using varied numbers of supplementary traini...
<p>The data set is partitioned into 10 parts (folds) in the outer loop. One fold of the data set is ...
Performance of different modules on training sets using 5-fold cross-validation.</p
<p>10-Fold Cross Validation Accuracy of classification methods with the addition of noisy variables....
<p>Classification rates using ten-fold cross-validation (10-fold) versus using only the 1<sup>st</su...
<p>Evaluation of regression algorithms on 10-fold cross-validation on the SICK training corpus.</p
Background: The bootstrap can be alternative to cross-validation as a training/test set splitting me...
<p>The number of misclassified samples for each run and the final accuracy using 10-fold cross-valid...
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
Cross-validation test results for the context-specific algorithms under study.</p
<p>10% of the data were defined as test dataset (TestData1) while the remaining 90% (TrainingData1) ...
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