(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Prediction of “Pathogenic” broader class versus “Benign” broader class and “VUS” class (C) Prediction of “VUS” class versus “Benign” broader class and “Pathogenic” broader class.</p
<p>Comparison of PredictSNP and its constituent tools with PredictSNP benchmark dataset (A). Compari...
<p>Comparison of disorder predictors in terms of (A) ROC curve and (B) precision-recall curve on CAS...
Best values of a performance score, across all classification tools, are shown in bold.</p
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
<p>Accuracy, F-measure (F1 Score), precision, recall, correlation coefficient (C.C.), and area under...
Precision recall curves for the top performing model compared to individual feature predictions.</p
<p>(a)–(e): precision-recall curves for different methods on <sup>15</sup>N-HSQC, HNCO, HNCA, CBCA(C...
<p>(<b>A</b>) ROCs of five different methods. The values in the brackets are the average auROCs of e...
<p>Comparison of prediction performance of classifiers in terms of AUC score, at different levels hi...
<p>The blue and the red curve indicate estimators of the best and the worst curve, respectively. The...
Average accuracy, recall, precision, MCC, and AUC measures over 10 folds for the three effector pred...
<p>A: Precision-recall curves of validation data sets. B: Precision-recall curves of test data sets....
<p>Comparison of various prediction methods in terms of the area under the ROC curve (AUC).</p
<p>Comparison of PredictSNP and its constituent tools with PredictSNP benchmark dataset (A). Compari...
<p>Comparison of disorder predictors in terms of (A) ROC curve and (B) precision-recall curve on CAS...
Best values of a performance score, across all classification tools, are shown in bold.</p
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
<p>Accuracy, F-measure (F1 Score), precision, recall, correlation coefficient (C.C.), and area under...
Precision recall curves for the top performing model compared to individual feature predictions.</p
<p>(a)–(e): precision-recall curves for different methods on <sup>15</sup>N-HSQC, HNCO, HNCA, CBCA(C...
<p>(<b>A</b>) ROCs of five different methods. The values in the brackets are the average auROCs of e...
<p>Comparison of prediction performance of classifiers in terms of AUC score, at different levels hi...
<p>The blue and the red curve indicate estimators of the best and the worst curve, respectively. The...
Average accuracy, recall, precision, MCC, and AUC measures over 10 folds for the three effector pred...
<p>A: Precision-recall curves of validation data sets. B: Precision-recall curves of test data sets....
<p>Comparison of various prediction methods in terms of the area under the ROC curve (AUC).</p
<p>Comparison of PredictSNP and its constituent tools with PredictSNP benchmark dataset (A). Compari...
<p>Comparison of disorder predictors in terms of (A) ROC curve and (B) precision-recall curve on CAS...
Best values of a performance score, across all classification tools, are shown in bold.</p