The best performances are indicated in bold (the lower the better). These results are obtained using 100-fold cross validation.</p
Performance of different models on PF2095 dataset using 10-fold cross-validation method.</p
<p>Comparative performance analysis of the rule-based classifiers on Dataset 2, respectively (at 4-f...
10-fold cross-validation mean classification performance for MCI against CN of multi-functional feat...
<p>Comparison of classification results obtained through 5-fold cross validation with respect to dif...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Each algorithm trained using selected features and evaluated with 10-fold cross-validation. Value...
<p>The correct rates (%) were derived with systematically varying number of labels (L), number of sa...
10-fold cross-validation mean classification performance for AD against CN of multi-functional featu...
<p>Comparison of classification performance (20 runs of 10-fold cross-validation) on 40 UCI datasets...
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
<p>The upper panel illustrates the combination of the inner cross-validation loop, which is used to ...
<p>10-Fold Cross Validation Accuracy of classification methods with the addition of noisy variables....
<p>Comparison of classification results obtained through class imbalance learning method with the op...
<p>Feature Selection (mean±std over 100 10-fold cross-validations, i.e. 1000 classification models)....
<p>Comparative performance analysis of the rule-based classifiers on Dataset 1, respectively (at 4-f...
Performance of different models on PF2095 dataset using 10-fold cross-validation method.</p
<p>Comparative performance analysis of the rule-based classifiers on Dataset 2, respectively (at 4-f...
10-fold cross-validation mean classification performance for MCI against CN of multi-functional feat...
<p>Comparison of classification results obtained through 5-fold cross validation with respect to dif...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Each algorithm trained using selected features and evaluated with 10-fold cross-validation. Value...
<p>The correct rates (%) were derived with systematically varying number of labels (L), number of sa...
10-fold cross-validation mean classification performance for AD against CN of multi-functional featu...
<p>Comparison of classification performance (20 runs of 10-fold cross-validation) on 40 UCI datasets...
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
<p>The upper panel illustrates the combination of the inner cross-validation loop, which is used to ...
<p>10-Fold Cross Validation Accuracy of classification methods with the addition of noisy variables....
<p>Comparison of classification results obtained through class imbalance learning method with the op...
<p>Feature Selection (mean±std over 100 10-fold cross-validations, i.e. 1000 classification models)....
<p>Comparative performance analysis of the rule-based classifiers on Dataset 1, respectively (at 4-f...
Performance of different models on PF2095 dataset using 10-fold cross-validation method.</p
<p>Comparative performance analysis of the rule-based classifiers on Dataset 2, respectively (at 4-f...
10-fold cross-validation mean classification performance for MCI against CN of multi-functional feat...
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