Figure 3.

Classifier performance is influenced by signature size, the number of informative cases and the number of features included in the prediction model. The numbers of spiked probes were 10, 25, 50 and 100 and the number of features included in the prediction model was set to 100. Log₂ fold-change ("c") was set to 0.5. The solid lines indicate the average area above the ROC curve (AAC) from Monte Carlo Cross Validation (MCCV), the dots represent results from the 20 individual iterations of the analysis performed on the MAQC-II data set (n = 233).