<p>ROC curves of different encoding SVM models using a leave-one-out cross-validation.</p
<p>The ROC curves based on three methods/models (TILoR: Blue line; GLM: Red line; random forest: Gre...
<p>ROC curves obtained with different feature sets extracted from the tumor region using (a) leave-o...
<p>ROC curves of hybrid models AAC+DPC, N5C5Bin, Physico and AAC+DPC+Physico+N5C5Bin developed by SV...
<p>ROC curves of different encoding SVM models using a 10-fold cross-validation.</p
<p>ROC curves of the single SVM models trained using various features based on five-fold cross-valid...
<p>ROC curves for the two models of the development set using leave-one-out cross-validation (LOOCV)...
<p>ROC Curve of different classification methods (SVM only, GA+SVM, GA+SVM+Post Spike Matching).</p
<p>The ROC curves of the RF and SVM in internal five-fold cross validation for (a) Model I, (b) Mode...
<p>For each threshold, we build a linear formula taking corresponding features and train dataset. Th...
The ROC curves for 2-folds, 4-folds, 10-folds, and leave one subject out cross validation experiment...
<p>The ROC curves of the RF and SVM in four independent external validations for (a) Model I, (b) Mo...
ROC curves of the methods with different images features and different classifiers: the proposed met...
<p>The ROC curve for leave-one-out cross validation and the AUC of our algorithm is 0.7645.</p
ROC curves of the methods with different features for representing images and different classifiers....
<p>The ROC curves of classifiers created on 48 original features (the blue solid line) and 25 featur...
<p>The ROC curves based on three methods/models (TILoR: Blue line; GLM: Red line; random forest: Gre...
<p>ROC curves obtained with different feature sets extracted from the tumor region using (a) leave-o...
<p>ROC curves of hybrid models AAC+DPC, N5C5Bin, Physico and AAC+DPC+Physico+N5C5Bin developed by SV...
<p>ROC curves of different encoding SVM models using a 10-fold cross-validation.</p
<p>ROC curves of the single SVM models trained using various features based on five-fold cross-valid...
<p>ROC curves for the two models of the development set using leave-one-out cross-validation (LOOCV)...
<p>ROC Curve of different classification methods (SVM only, GA+SVM, GA+SVM+Post Spike Matching).</p
<p>The ROC curves of the RF and SVM in internal five-fold cross validation for (a) Model I, (b) Mode...
<p>For each threshold, we build a linear formula taking corresponding features and train dataset. Th...
The ROC curves for 2-folds, 4-folds, 10-folds, and leave one subject out cross validation experiment...
<p>The ROC curves of the RF and SVM in four independent external validations for (a) Model I, (b) Mo...
ROC curves of the methods with different images features and different classifiers: the proposed met...
<p>The ROC curve for leave-one-out cross validation and the AUC of our algorithm is 0.7645.</p
ROC curves of the methods with different features for representing images and different classifiers....
<p>The ROC curves of classifiers created on 48 original features (the blue solid line) and 25 featur...
<p>The ROC curves based on three methods/models (TILoR: Blue line; GLM: Red line; random forest: Gre...
<p>ROC curves obtained with different feature sets extracted from the tumor region using (a) leave-o...
<p>ROC curves of hybrid models AAC+DPC, N5C5Bin, Physico and AAC+DPC+Physico+N5C5Bin developed by SV...
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