Figure 3
Distribution of the percentage of misclassified samples across different ‘RHI’ scores. Fifty-four classifiers (summarized in Figure 2 and Supplementary Table 1 online) were plotted in three panels based on the classification algorithm that was used: (a) nearest centriod (NC); (b) K-nearest neighbor (KNN); and (c) decision forest (DF). AFX → AFX (or AGL → AGL) denotes the prediction results to the test set that were obtained when the signature genes were generated using the Affymetrix (or Agilent) training set from the same platform. In contrast, AFX → AGL (or AGL → AFX) indicates that the signature genes had been identified using the training set from the opposite platform. No samples with an RHI score >2 was misclassified in any of the permutations tested. The largest misclassification rate was observed for low RHI scores (that is, RHI=0 and 1), relating to either the absence of any apparent or the presence of only minor amounts of liver injury.
