<p>(A) Cross-validation (CV) performance of models trained on all available native IRES sequences shown for different combinations of <i>k</i>-mer lengths, and <i>k</i>-mer count (solid lines) or presence (dashed lines) features (left), with the selected combination marked with a circle. Scatter plot of predicted and true IRES activities for the selected model (middle) coloured according to the local density (blue to red as low to high density). The Receiver Operating Characteristic (ROC) curve and the area under the curve (AUC) for the selected combination. (B) CV performance of models trained for different groups of sequences. Only results for groups with models achieving sufficiently high performance are shown. (C) Training and test perf...
<p>A: The results of 2-fold cross validations are shown for each regression method in this in this f...
<p>The prediction performance of the final model using 18 features, by 10-fold cross validation.</p
<p>D<sup>2</sup>: explained predictive deviance</p><p>AUC: area under the receiver operating curve (...
<p><b>(A)</b> Receiver operating characteristic (ROC) curve. The solid black line indicates the medi...
<p><b>(a)</b> The ensemble-based prediction model based on all five combined patterns has an area un...
<p>Performance on the benchmark training dataset was evaluated based on AUC, MCC, Accuracy, Specific...
a:<p>ten-fold cross-validation of 3845 entries.</p>b:<p>independent test (1508 entries) by training ...
<p>Results are showed on simple and complex traits through the 10 replicates of the simulation. Figu...
<p>Red, blue, and green curve denotes 5-fold cross-validation prediction performance of Bi-profile B...
<p>A) Discovery data (32,587 SNPs) B) Combined data (32,375 SNPs). Ten sets of training and testing ...
<p>Receiver operating characteristic (ROC) curves, and corresponding areas under the curves (AUC) wi...
<p>Prediction performance of CoReCo phases I and II, naive Bayesian classifier and individual BLAST ...
Reliable estimation of the classification performance of inferred predictive models is difficult whe...
<p>The experiment was conducted 10 times using 10-fold cross-validation performed on the training se...
<p>(A) The isolates predicted were not included in the training set, still performance is robust. Ba...
<p>A: The results of 2-fold cross validations are shown for each regression method in this in this f...
<p>The prediction performance of the final model using 18 features, by 10-fold cross validation.</p
<p>D<sup>2</sup>: explained predictive deviance</p><p>AUC: area under the receiver operating curve (...
<p><b>(A)</b> Receiver operating characteristic (ROC) curve. The solid black line indicates the medi...
<p><b>(a)</b> The ensemble-based prediction model based on all five combined patterns has an area un...
<p>Performance on the benchmark training dataset was evaluated based on AUC, MCC, Accuracy, Specific...
a:<p>ten-fold cross-validation of 3845 entries.</p>b:<p>independent test (1508 entries) by training ...
<p>Results are showed on simple and complex traits through the 10 replicates of the simulation. Figu...
<p>Red, blue, and green curve denotes 5-fold cross-validation prediction performance of Bi-profile B...
<p>A) Discovery data (32,587 SNPs) B) Combined data (32,375 SNPs). Ten sets of training and testing ...
<p>Receiver operating characteristic (ROC) curves, and corresponding areas under the curves (AUC) wi...
<p>Prediction performance of CoReCo phases I and II, naive Bayesian classifier and individual BLAST ...
Reliable estimation of the classification performance of inferred predictive models is difficult whe...
<p>The experiment was conducted 10 times using 10-fold cross-validation performed on the training se...
<p>(A) The isolates predicted were not included in the training set, still performance is robust. Ba...
<p>A: The results of 2-fold cross validations are shown for each regression method in this in this f...
<p>The prediction performance of the final model using 18 features, by 10-fold cross validation.</p
<p>D<sup>2</sup>: explained predictive deviance</p><p>AUC: area under the receiver operating curve (...