<p>(a) Estimated predictive performance from the outer cross-validation (internal) and obtained by applying the constructed classifier to an external test set (external). (b) The fraction of predictor variables selected for the final classifier that were simulated to be differentially expressed and/or associated with the batch. The bars summarize results across all classifiers and all data set replicates. The bar heights represent the average fraction of variables extracted from each category, and the error bars extend one standard deviation above the average.</p
<p>We compared the performance of the single genes classifier trained on all genes present on the mi...
<p>(A) The ROC curve illustrating the performance for full transcript mode. (B) The ROC curve illust...
Abstract Background Machine learning models (classifiers) for classifying genes to biological proces...
<p>(a) Estimated predictive performance from the outer cross-validation (internal) and obtained by a...
<p>(a) Estimated predictive performance from the outer cross-validation (internal) and obtained by a...
With the large amount of biological data that is currently publicly available, many investigators co...
With the large amount of biological data that is currently publicly available, many investigators co...
<p>The column “%CV-support” in the table indicates the percentage of the cross-validation training s...
<p>Comparison of prediction accuracy on four multiclass classification datasets by varying the numbe...
Motivation: Class predicting with gene expression is widely used to generate diagnostic and/or progn...
The effect of Combat harmonization in the external validation dataset on model performance per machi...
<p>Comparison of prediction accuracy on four binary classification datasets by varying the number of...
<p>The upper panel illustrates the combination of the inner cross-validation loop, which is used to ...
<p>Results for different basic classifiers (mean±SD) by using varied numbers of supplementary traini...
<p>The full dataset is a gene expression matrix with 8,000 features (the genes) as rows and 30 sampl...
<p>We compared the performance of the single genes classifier trained on all genes present on the mi...
<p>(A) The ROC curve illustrating the performance for full transcript mode. (B) The ROC curve illust...
Abstract Background Machine learning models (classifiers) for classifying genes to biological proces...
<p>(a) Estimated predictive performance from the outer cross-validation (internal) and obtained by a...
<p>(a) Estimated predictive performance from the outer cross-validation (internal) and obtained by a...
With the large amount of biological data that is currently publicly available, many investigators co...
With the large amount of biological data that is currently publicly available, many investigators co...
<p>The column “%CV-support” in the table indicates the percentage of the cross-validation training s...
<p>Comparison of prediction accuracy on four multiclass classification datasets by varying the numbe...
Motivation: Class predicting with gene expression is widely used to generate diagnostic and/or progn...
The effect of Combat harmonization in the external validation dataset on model performance per machi...
<p>Comparison of prediction accuracy on four binary classification datasets by varying the number of...
<p>The upper panel illustrates the combination of the inner cross-validation loop, which is used to ...
<p>Results for different basic classifiers (mean±SD) by using varied numbers of supplementary traini...
<p>The full dataset is a gene expression matrix with 8,000 features (the genes) as rows and 30 sampl...
<p>We compared the performance of the single genes classifier trained on all genes present on the mi...
<p>(A) The ROC curve illustrating the performance for full transcript mode. (B) The ROC curve illust...
Abstract Background Machine learning models (classifiers) for classifying genes to biological proces...