Table 8. cont. 5-Protein Signature Classifier Dataset size IB1 Ibk Kstar LWL AdaBoost ClassViaRegression Decorate* MultiClass Classifier Random Committee* j48 LMT NBTree Part Random Forest* Ordinal Classifier Average Agreement (%) 18 protein Sig. 10 protein Sig. 6 protein Sig. 5 protein Sig. Error Avg Agr % Error Avg Agr % Error Avg Agr % Error Avg Agr % 139 24.34 82% 25.98 81% 24.44 82% 23.20 83% 139 30 30 26 29 31 24 21.8 20 26.1 24 18 21 27 26.2 24 23.20 83% 64 10 10 8 16 3 5 8.7 4 10.9 10 4 10 13 12.1 10 7.71 88% 64 9.02 86% 82% 7.83 88% 81% 8.60 87% 82% 7.71 88% 83% 22 7 7 5 10 2 4 7 4 7.8 8 4 9 10 8.9 8 5.93 73% 22 5.36 76% 66% 5.38 76% 66% 6.58 70% 64% 5.93 73% 65% Alzheimer 25 13 13 11 10 17 12 9.2 10 10.1 9 10 9 9 9.2 9 10.73 57% 25 10.53 58% 10.52 58% 10.14 59% 10.73 57% Grand Total OVERALL (‘‘AD’’+‘‘MCI’’) AD Er. NAD Er. Test Set ‘‘AD’’ AD Er. Test Set ‘‘MCI’’ NAD Er. AD Er. NAD Er. 75 20 20 18 13 28 19 13.1 16 15.2 14 14 11 14 14.1 14 15.49 79.4% 75 15.33 80% 18.15 76% 15.84 79% 15.49 79% 42 3 3 3 6 1 1 1.7 0 3.1 2 0 1 3 3.2 2 1.78 96% 42 3.66 91% 91% 2.45 94% 89% 2.02 95% 92% 1.78 96% 93% 50 7 7 7 3 11 7 3.9 6 5.1 5 4 2 5 4.9 5 4.75 90% 50 4.79 90% 7.64 85% 5.70 89% 4.75 90% Removing IL-6 from the biomarker set we have a small gain in predicting AD in both data set, if compared to the 6-protein signature. In this case, the prediction of AD on the ‘‘AD’’ test set achieves an average of 96% without dropping the accuracy of the prediction of NonAD. doi:10.1371/journal.pone.0003111.t008 Nevertheless, with these tests our objective is to show the robustness of our methods to discovery biomarkers, by showing the independence of the signature performance from the selected classifier. It is interesting to note that the mathematical model and algorithms we have used have pointed at Interleukin-6 and included it in the 10-protein signature. It is well known that IL- 6 with other cytokines have been the subject of many studies of Table 9. Average results for each signature over 24 classifiers. Size Overall Overall (‘‘AD’’+‘‘MCI’’) AD Er. NAD Er. Test set ‘‘AD’’ Test set ‘‘MCI’’ AD Er. NAD Er. AD Er. NAD Er. For each signature the average number of errors is reported and the percentage agreement is calculated over each specific population. The best results are highlighted in bold text. doi:10.1371/journal.pone.0003111.t009 PLoS ONE | www.plosone.org 8 September 2008 | Volume 3 | Issue 9 | e3111