<p>Performance assessment of structural and functional residue predictors using cross-validation on positive-unlabeled data sets.</p
<p>Prediction performance of leave-one-out cross-validation based on different encoding methods.</p
<p>Prediction performance in leave-one-out cross validation based on metabolites selected by LASSO o...
*<p>The latter number represents standard deviation from 10 training set;</p>**<p>the lower right co...
<p>ISMBLab-LIG residue-based prediction performances benchmarked with published datasets.</p
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
<p>The prediction performance of the final model using 18 features, by 10-fold cross validation.</p
<p>Predictive performance of the four types of zinc-binding residues (CHED) of our method, SitePredi...
Performance of different modules on training sets using 5-fold cross-validation.</p
Performance of different models on PF4204 dataset using 10-fold cross-validation method.</p
Performance metrics of the prediction models using logistic regression and random forest methods wit...
<p>Performance of meta-predictors under multi-fold cross validation and in independent dataset under...
<p>The predictive models were optimized using the combined set of interactions and evaluated with ne...
Performance of different models on PF2095 dataset using 10-fold cross-validation method.</p
<p>The performance of the binary encoding scheme was assessed using a 10-fold cross-validation strat...
<p>The prediction results compared with other methods on the training dataset using 10-fold cross-va...
<p>Prediction performance of leave-one-out cross-validation based on different encoding methods.</p
<p>Prediction performance in leave-one-out cross validation based on metabolites selected by LASSO o...
*<p>The latter number represents standard deviation from 10 training set;</p>**<p>the lower right co...
<p>ISMBLab-LIG residue-based prediction performances benchmarked with published datasets.</p
<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
<p>The prediction performance of the final model using 18 features, by 10-fold cross validation.</p
<p>Predictive performance of the four types of zinc-binding residues (CHED) of our method, SitePredi...
Performance of different modules on training sets using 5-fold cross-validation.</p
Performance of different models on PF4204 dataset using 10-fold cross-validation method.</p
Performance metrics of the prediction models using logistic regression and random forest methods wit...
<p>Performance of meta-predictors under multi-fold cross validation and in independent dataset under...
<p>The predictive models were optimized using the combined set of interactions and evaluated with ne...
Performance of different models on PF2095 dataset using 10-fold cross-validation method.</p
<p>The performance of the binary encoding scheme was assessed using a 10-fold cross-validation strat...
<p>The prediction results compared with other methods on the training dataset using 10-fold cross-va...
<p>Prediction performance of leave-one-out cross-validation based on different encoding methods.</p
<p>Prediction performance in leave-one-out cross validation based on metabolites selected by LASSO o...
*<p>The latter number represents standard deviation from 10 training set;</p>**<p>the lower right co...