<p>(a) Values for TPR, TNR, PPV, and NPV. (b) Values for MCC, BACC, AUC, and ACC.</p
a<p>The overall recognition accuracy is 97.40±0.95%.</p>b<p>The class precision is the percentage of...
<p>AAC, Amino Acid Composition; DPC, Di Peptide Composition; N5AAC, Amino Acid Composition of 5 N-te...
<p>SVM based performance on testing dataset (5-fold cross-validation) using parameters t = 2 (RBF ke...
<p>(a) ACC, (b) BACC, (c) MCC, and (d) AUC of five SVM models trained on 5 different data sets (trai...
<p>(a) TPR, (b) NPR, (c) PPV, and (d) NPV of five SVM models trained on 5 different data sets (train...
<p>Total 1783 cysteine sequences were applied in positive and negative data. Sn, sensitivity; Sp, sp...
<p>The generalized performance of the SVM model. We rebuilt the model for 100 times for the validati...
<p>D: dimensionality; AUC: area under ROC curve; Spe: specificity; Pre: precision; Sen: sensitivity;...
<p>The 10-fold cross-validation results of independent test by SVM algorithm with g = 0.005 and cuto...
In part (A) the ROC curves of the two methods are relative to the prediction of increasing and decre...
<p>. One set of models was fitted with cross-validation (CV) and the other without.</p
<p>Parameters for the various SVR models which were found through 10-fold cross-validation using a g...
a<p>The 13 feature schemes were: where <i>k</i> = {<i>1</i>,<i>5</i>,<i>6</i>,<i>7</i>}, <i>g</i> =...
<p>The results have been run 20 times for every feature construction by SVM algorithm with g = 0.005...
Diagnostic ability of the LR, SVM, and MLP models in the cross-validation set.</p
a<p>The overall recognition accuracy is 97.40±0.95%.</p>b<p>The class precision is the percentage of...
<p>AAC, Amino Acid Composition; DPC, Di Peptide Composition; N5AAC, Amino Acid Composition of 5 N-te...
<p>SVM based performance on testing dataset (5-fold cross-validation) using parameters t = 2 (RBF ke...
<p>(a) ACC, (b) BACC, (c) MCC, and (d) AUC of five SVM models trained on 5 different data sets (trai...
<p>(a) TPR, (b) NPR, (c) PPV, and (d) NPV of five SVM models trained on 5 different data sets (train...
<p>Total 1783 cysteine sequences were applied in positive and negative data. Sn, sensitivity; Sp, sp...
<p>The generalized performance of the SVM model. We rebuilt the model for 100 times for the validati...
<p>D: dimensionality; AUC: area under ROC curve; Spe: specificity; Pre: precision; Sen: sensitivity;...
<p>The 10-fold cross-validation results of independent test by SVM algorithm with g = 0.005 and cuto...
In part (A) the ROC curves of the two methods are relative to the prediction of increasing and decre...
<p>. One set of models was fitted with cross-validation (CV) and the other without.</p
<p>Parameters for the various SVR models which were found through 10-fold cross-validation using a g...
a<p>The 13 feature schemes were: where <i>k</i> = {<i>1</i>,<i>5</i>,<i>6</i>,<i>7</i>}, <i>g</i> =...
<p>The results have been run 20 times for every feature construction by SVM algorithm with g = 0.005...
Diagnostic ability of the LR, SVM, and MLP models in the cross-validation set.</p
a<p>The overall recognition accuracy is 97.40±0.95%.</p>b<p>The class precision is the percentage of...
<p>AAC, Amino Acid Composition; DPC, Di Peptide Composition; N5AAC, Amino Acid Composition of 5 N-te...
<p>SVM based performance on testing dataset (5-fold cross-validation) using parameters t = 2 (RBF ke...
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