10.1371/journal.pone.0055895.t002 Matthew A. Care Matthew A. Care Sharon Barrans Sharon Barrans Lisa Worrillow Lisa Worrillow Andrew Jack Andrew Jack David R. Westhead David R. Westhead Reuben M. Tooze Reuben M. Tooze Assessment of machine-learning tool meta-classifiers combined with balanced voting. Public Library of Science 2013 machine-learning meta-classifiers 2013-02-12 00:30:06 Dataset https://plos.figshare.com/articles/dataset/_Assessment_of_machine_learning_tool_meta_classifiers_combined_with_balanced_voting_/161806 <p>Machine-learning tools were combined using balanced voting to generate meta-classifiers. The best 6 individual classifiers were combined, and with iterative cycles of classifier removal 5, 4, 3 and 2 machine-learning tool meta-classifiers were tested. Survival separation between assigned ABC and GCB classes for the data sets GSE32918, and GSE10846 divided into CHOP and R-CHOP components was used for assessment. The classifiers were ordered by their average rank across the data sets; with rank determined by the p-value of the ABC/GCB separation. The Classifier Identity, Hazard Ratio (vs ABC as baseline), 95% confidence interval of the Hazard Ratio, and the resulting p-value for survival separation are shown.</p>