<p>The bar charts show the average AUCs of within-dataset experiments for five pathway-based methods (LLR, CORG, PCA, mean, and median) and a gene-based method. In these experiments, the top 50 pathways have been reselected in every experiment using the designated training set. (A) Classification results based on logistic regression. (B) Classification results based on LDA (linear discriminant analysis).</p
<p>Comparisons of the classification performance of classic GS and MiNeGS approaches, using ROC AUC ...
<p>Performance, expressed in percentages, of the four approaches presented in this study. NB1 and LR...
<p>For each user and the grand average (GA), the performances of three experimental blocks are given...
<p>The bar charts show the average AUCs for different classification methods. Five pathway-based met...
This research uses four classification algorithms in standard and boosted forms to predict members o...
In this paper we show the results of a comparison simulation study for three classification techniqu...
<p>Influence of secondary data sources and classifier combination on classification performance. The...
We analyzed the performance of LDA, Quadratic Discriminant Analysis (QDA), K-Nearest Neighbours (KNN...
<p>Average test AUC values under best training for classifiers or combined classifiers, each built o...
This study compares the classification accuracy of linear discriminant analysis (LDA), quadratic dis...
A) ROC curves for compound-wise rankings (gray curves) and compound-aggregated rankings (coloured cu...
<p>The table shows the median classifier performance (AUC) of the classification problems considerin...
<p>(A) Mean absolute -score of the top markers for the Netherlands breast cancer dataset. Pathway a...
<p>For each predictor, the AUC obtained in the training and validation sets, as well as the 95% Conf...
<p><b>A</b> AUC. <b>B</b> Accuracy. Performances are visualized for all 190 evenly distributed in si...
<p>Comparisons of the classification performance of classic GS and MiNeGS approaches, using ROC AUC ...
<p>Performance, expressed in percentages, of the four approaches presented in this study. NB1 and LR...
<p>For each user and the grand average (GA), the performances of three experimental blocks are given...
<p>The bar charts show the average AUCs for different classification methods. Five pathway-based met...
This research uses four classification algorithms in standard and boosted forms to predict members o...
In this paper we show the results of a comparison simulation study for three classification techniqu...
<p>Influence of secondary data sources and classifier combination on classification performance. The...
We analyzed the performance of LDA, Quadratic Discriminant Analysis (QDA), K-Nearest Neighbours (KNN...
<p>Average test AUC values under best training for classifiers or combined classifiers, each built o...
This study compares the classification accuracy of linear discriminant analysis (LDA), quadratic dis...
A) ROC curves for compound-wise rankings (gray curves) and compound-aggregated rankings (coloured cu...
<p>The table shows the median classifier performance (AUC) of the classification problems considerin...
<p>(A) Mean absolute -score of the top markers for the Netherlands breast cancer dataset. Pathway a...
<p>For each predictor, the AUC obtained in the training and validation sets, as well as the 95% Conf...
<p><b>A</b> AUC. <b>B</b> Accuracy. Performances are visualized for all 190 evenly distributed in si...
<p>Comparisons of the classification performance of classic GS and MiNeGS approaches, using ROC AUC ...
<p>Performance, expressed in percentages, of the four approaches presented in this study. NB1 and LR...
<p>For each user and the grand average (GA), the performances of three experimental blocks are given...