Figure 6.

Frequency of occurrence of features in voting classifiers. Frequency of occurrence of features used in voting classifiers containing 51 features across 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.