<p>Each value is averaged over 100 independent runs with random divisions of training set and probe set . The bold font represents that MI is better than the corresponding prediction index.</p><p>Comparison of the prediction accuracy measured by precision (top-100) on ten real-world networks.</p
<p>Comparison of the training time and forecasting accuracy (training 40%, testing 60%).</p
<p>These calculations assume that both the full-data and real-time multi-step predictions began at t...
<p>Results for the hyperparameters that achieved the highest correlation coefficients (see <a href="...
<p>Each value is averaged over 100 independent runs with random divisions of training set and probe...
<p>The average precision for active learning versus most confident (MC) prediction selection.</p
Accuracy comparisons of ten experiments with SVM, KNN, BPNN, CNN, ResNet, FA+ResNet models.</p
Comparison results of different network models: A is training accuracy of model, B is validation acc...
<p>Each data point is obtained by averaging over ten runs, each of which has an independently random...
<p>The <i>testMSEs</i> comparisons of prediction performance for four networks.</p
<p>Pr1Rec, Pr10Rec, Pr50Rec, Pr80Rec represent precision at 1%, 10%, 50%, and 80% recall when all (<...
Comparison of accuracy for different approaches, where small value indicates good performance and bo...
<p>The experiment was conducted 10 times using 10-fold cross-validation performed on the training se...
<p>Pr1Rec, Pr10Rec, Pr50Rec, Pr80Rec represent precision at 1%, 10%, 50%, and 80% recall. The last r...
<p>Sn: sensitivity (recall).</p><p>Pr: precision.</p><p>Sp: specificity.</p><p>Ac: accuracy.</p><p>M...
<p>This table reports average <i>F</i><sub>1</sub>, Precision, Recall scores of five methods in thre...
<p>Comparison of the training time and forecasting accuracy (training 40%, testing 60%).</p
<p>These calculations assume that both the full-data and real-time multi-step predictions began at t...
<p>Results for the hyperparameters that achieved the highest correlation coefficients (see <a href="...
<p>Each value is averaged over 100 independent runs with random divisions of training set and probe...
<p>The average precision for active learning versus most confident (MC) prediction selection.</p
Accuracy comparisons of ten experiments with SVM, KNN, BPNN, CNN, ResNet, FA+ResNet models.</p
Comparison results of different network models: A is training accuracy of model, B is validation acc...
<p>Each data point is obtained by averaging over ten runs, each of which has an independently random...
<p>The <i>testMSEs</i> comparisons of prediction performance for four networks.</p
<p>Pr1Rec, Pr10Rec, Pr50Rec, Pr80Rec represent precision at 1%, 10%, 50%, and 80% recall when all (<...
Comparison of accuracy for different approaches, where small value indicates good performance and bo...
<p>The experiment was conducted 10 times using 10-fold cross-validation performed on the training se...
<p>Pr1Rec, Pr10Rec, Pr50Rec, Pr80Rec represent precision at 1%, 10%, 50%, and 80% recall. The last r...
<p>Sn: sensitivity (recall).</p><p>Pr: precision.</p><p>Sp: specificity.</p><p>Ac: accuracy.</p><p>M...
<p>This table reports average <i>F</i><sub>1</sub>, Precision, Recall scores of five methods in thre...
<p>Comparison of the training time and forecasting accuracy (training 40%, testing 60%).</p
<p>These calculations assume that both the full-data and real-time multi-step predictions began at t...
<p>Results for the hyperparameters that achieved the highest correlation coefficients (see <a href="...
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