%0 Generic %A A. Care, Matthew %A Barrans, Sharon %A Worrillow, Lisa %A Jack, Andrew %A R. Westhead, David %A M. Tooze, Reuben %D 2013 %T Assessment of machine-learning tool meta-classifiers combined with balanced voting. %U https://plos.figshare.com/articles/dataset/_Assessment_of_machine_learning_tool_meta_classifiers_combined_with_balanced_voting_/161806 %R 10.1371/journal.pone.0055895.t002 %2 https://plos.figshare.com/ndownloader/files/491287 %K machine-learning %K meta-classifiers %X

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.

%I PLOS ONE