<p>The classification rate and ROC values with and without feature selection.</p
<p>Performance evaluation of various classifier and feature selection methods.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
<p>ROC Curve of different classification methods (SVM only, GA+SVM, GA+SVM+Post Spike Matching).</p
ROC curves of the model under non-feature selection, feature selection, and mixed sampling.</p
<p>Receiver operating characteristic (ROC) curve for different classification methods on the test se...
<p>Receiver operating characteristic (ROC) curve for different classification methods on the trainin...
ROC curves of the methods with different features for representing images and different classifiers....
<p>ROC curves for the best result in Experiment 4 (Non correlated features at 97%).</p
<p>ROC curve for the best model found on the reduced feature set (discovery).</p
<p>The ROC graph is plotted to show the performance of the binary classifiers.</p
<p>Comparison results of classification performance between ELM with and without feature selection.<...
<p>ROC curve and AUC values for CBFS and Lect feature selection algorithms on Prostate dataset.</p
<p>Features sorted by the percentage of missing values, with the two “knees” chosen as thresholds fo...
<p>ROC curve for the best model found on the reduced feature set (replication).</p
<p>ROC analysis results for discriminating multiple fallers from non-fallers.</p
<p>Performance evaluation of various classifier and feature selection methods.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
<p>ROC Curve of different classification methods (SVM only, GA+SVM, GA+SVM+Post Spike Matching).</p
ROC curves of the model under non-feature selection, feature selection, and mixed sampling.</p
<p>Receiver operating characteristic (ROC) curve for different classification methods on the test se...
<p>Receiver operating characteristic (ROC) curve for different classification methods on the trainin...
ROC curves of the methods with different features for representing images and different classifiers....
<p>ROC curves for the best result in Experiment 4 (Non correlated features at 97%).</p
<p>ROC curve for the best model found on the reduced feature set (discovery).</p
<p>The ROC graph is plotted to show the performance of the binary classifiers.</p
<p>Comparison results of classification performance between ELM with and without feature selection.<...
<p>ROC curve and AUC values for CBFS and Lect feature selection algorithms on Prostate dataset.</p
<p>Features sorted by the percentage of missing values, with the two “knees” chosen as thresholds fo...
<p>ROC curve for the best model found on the reduced feature set (replication).</p
<p>ROC analysis results for discriminating multiple fallers from non-fallers.</p
<p>Performance evaluation of various classifier and feature selection methods.</p
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
<p>ROC Curve of different classification methods (SVM only, GA+SVM, GA+SVM+Post Spike Matching).</p
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