Figure 1.

Multiple random validation results for voting classifiers. Mean accuracy for voting classifiers (unweighted and weighted) with varying numbers of features included in the classifier based on 1,000 random training:test set partitions of two gene expression data sets (leukemia, lung cancer) and a proteomics data set (prostate cancer). Features to include in the classifiers were identified through a jackknife procedure through which features were ranked according to their frequency of occurrence in the top 1% or 5% most significant features based on t-statistics across all jackknife samples.