<p>Prediction performance of 10-fold cross-validation based on different encoding methods.</p
Prediction performance comparison between using stack, concatenation, and novel difference block.</p
a:<p>ten-fold cross-validation of 3845 entries.</p>b:<p>independent test (1508 entries) by training ...
<p>For the MLR, ANN and RF methods, 95% confidence intervals of the difference between the indicator...
<p>Prediction performance of leave-one-out cross-validation based on different encoding methods.</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>The prediction performance of the final model using 18 features, by 10-fold cross validation.</p
<p>Performance comparison among various types of sequence features and methods for the across-germli...
Performance of different models on PF2095 dataset using 10-fold cross-validation method.</p
Performance of different models on PF4204 dataset using 10-fold cross-validation method.</p
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Performance assessment of structural and functional residue predictors using cross-validation on ...
Accuracy measures for 10-fold cross-validation of Model 1 using the entire feature set for predictio...
Performance of different modules on training sets using 5-fold cross-validation.</p
<p>Prediction performance of computational methods in various folds, superfamilies and families.</p
Prediction performance comparison between using stack, concatenation, and novel difference block.</p
a:<p>ten-fold cross-validation of 3845 entries.</p>b:<p>independent test (1508 entries) by training ...
<p>For the MLR, ANN and RF methods, 95% confidence intervals of the difference between the indicator...
<p>Prediction performance of leave-one-out cross-validation based on different encoding methods.</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>The prediction performance of the final model using 18 features, by 10-fold cross validation.</p
<p>Performance comparison among various types of sequence features and methods for the across-germli...
Performance of different models on PF2095 dataset using 10-fold cross-validation method.</p
Performance of different models on PF4204 dataset using 10-fold cross-validation method.</p
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Performance assessment of structural and functional residue predictors using cross-validation on ...
Accuracy measures for 10-fold cross-validation of Model 1 using the entire feature set for predictio...
Performance of different modules on training sets using 5-fold cross-validation.</p
<p>Prediction performance of computational methods in various folds, superfamilies and families.</p
Prediction performance comparison between using stack, concatenation, and novel difference block.</p
a:<p>ten-fold cross-validation of 3845 entries.</p>b:<p>independent test (1508 entries) by training ...
<p>For the MLR, ANN and RF methods, 95% confidence intervals of the difference between the indicator...
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