<p>Comparison of AUC accuracies on the four microarray datasets estimated using the 0.632+ bootstrap method with 100 bootstrap samples. (a) Colon dataset, (b) Breast2 dataset, (c) Breast3 dataset, and (d) NCI dataset.</p
<p>AUC Curves for the Different Machine Learning Models using SMOTE and evaluated using holdout (70/...
<p>Each value is averaged over 100 independent runs with random divisions of training set and probe...
<p>In these plots, the y-axis shows the performance of the reconstructed network, measured by the AU...
<p>Boxplots depicting AUC improvement across multiple factors (boxes above zero represent improvemen...
<p>Evaluations are made using randomly withheld test data without and with correcting geographical s...
<p><b>Copyright information:</b></p><p>Taken from "Stratification bias in low signal microarray stud...
<p>Continuous and dashed lines correspond to AUC = 0.5 or ratio = 1 and AUC = 0.7or ratio = 1.5 resp...
<p>In the boxplot, from bottom to top, they are Q1-1.5*IQR, Q1, median, Q3, and Q3+1.5*Q3 where Q1 i...
<p>The values were calculated over the 10 repetitions using 100 randomly selected chains from the SE...
<p>AUC scores for three different classifiers with different types of markers for Metagene and CoMi ...
<p>A. ROC curves for the experimental results on the benchmark set and a random set. It shows 1-spec...
<p>AUC scores of the models with the variation of <i>δ</i> on <i>Human</i> dataset.</p
B) DE. We measured performance using AUC of the ROC curve, plotted as a function of and . Pseudocolo...
<p>Influence of secondary data sources and classifier combination on classification performance. The...
<p>AUC analysis for the top 15 multidimensional biomarkers in the training and testing set.</p
<p>AUC Curves for the Different Machine Learning Models using SMOTE and evaluated using holdout (70/...
<p>Each value is averaged over 100 independent runs with random divisions of training set and probe...
<p>In these plots, the y-axis shows the performance of the reconstructed network, measured by the AU...
<p>Boxplots depicting AUC improvement across multiple factors (boxes above zero represent improvemen...
<p>Evaluations are made using randomly withheld test data without and with correcting geographical s...
<p><b>Copyright information:</b></p><p>Taken from "Stratification bias in low signal microarray stud...
<p>Continuous and dashed lines correspond to AUC = 0.5 or ratio = 1 and AUC = 0.7or ratio = 1.5 resp...
<p>In the boxplot, from bottom to top, they are Q1-1.5*IQR, Q1, median, Q3, and Q3+1.5*Q3 where Q1 i...
<p>The values were calculated over the 10 repetitions using 100 randomly selected chains from the SE...
<p>AUC scores for three different classifiers with different types of markers for Metagene and CoMi ...
<p>A. ROC curves for the experimental results on the benchmark set and a random set. It shows 1-spec...
<p>AUC scores of the models with the variation of <i>δ</i> on <i>Human</i> dataset.</p
B) DE. We measured performance using AUC of the ROC curve, plotted as a function of and . Pseudocolo...
<p>Influence of secondary data sources and classifier combination on classification performance. The...
<p>AUC analysis for the top 15 multidimensional biomarkers in the training and testing set.</p
<p>AUC Curves for the Different Machine Learning Models using SMOTE and evaluated using holdout (70/...
<p>Each value is averaged over 100 independent runs with random divisions of training set and probe...
<p>In these plots, the y-axis shows the performance of the reconstructed network, measured by the AU...
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