We have compared the prediction accuracy of the best-ranked projections found by VizRank to four standard machine learning methods: support vector machines (SVM, with linear kernel), k-nearest neighbors (with k set to square root of the number of training instances), naive Bayesian classifier, and decision trees (Quinlan's C4.5 implementation used with the default parameters). The predictive accuracy was assessed on six cancer gene expression data sets using the bootstrap resampling repeated 100 times, as recommended by (Braga-Neto and Dougherty, 2003). The final performance scores were computed using the 0.632 bootstrap estimator as suggested in the same reference. The average classification accuracies derived in this way and the area under the ROC curve, with their respective standard deviations are shown in the following tables.
| Data set | VizRank | SVM | k-NN | Naive Bayes | Decision trees |
| Leukemia | 96.40 +- 4.33 | 97.57 +- 3.71 | 92.72 +- 6.74 | 84.34 +- 10.33 | 90.46 +- 5.52 |
| DLBCL | 93.03 +- 5.67 | 97.85 +- 3.26 | 88.60 +- 6.29 | 83.76 +- 8.64 | 85.46 +- 9.10 |
| Prostate | 94.00 +- 4.53 | 93.47 +- 4.60 | 84.51 +- 6.58 | 81.10 +- 9.00 | 85.47 +- 7.77 |
| MLL | 95.00 +- 5.12 | 97.32 +- 3.21 | 89.65 +- 6.37 | 75.20 +- 9.67 | 88.31 +- 9.16 |
| SRBCT | 96.39 +- 5.01 | 99.42 +- 2.35 | 86.29 +- 6.96 | 75.31 +- 10.58 | 87.32 +- 8.00 |
| Lung cancer | 92.72 +- 3.40 | 94.67 +- 3.16 | 90.35 +- 3.44 | 75.28 +- 5.18 | 91.21 +- 5.09 |
| Ranks | 1.83 | 1.17 | 3.5 | 5.00 | 3.50 |
| Data set | VizRank | SVM | k-NN | Naive Bayes | Decision trees |
| Leukemia | 0.976 +- 0.040 | 0.997 +- 0.011 | 0.969 +- 0.049 | 0.819 +- 0.127 | 0.903 +- 0.069 |
| DLBCL | 0.946 +- 0.077 | 0.997 +- 0.010 | 0.925 +- 0.058 | 0.736 +- 0.095 | 0.818 +- 0.118 |
| Prostate | 0.961 +- 0.036 | 0.973 +- 0.026 | 0.912 +- 0.051 | 0.835 +- 0.091 | 0.870 +- 0.075 |
| MLL | 0.981 +- 0.030 | 0.998 +- 0.005 | 0.983 +- 0.020 | 0.860 +- 0.073 | 0.938 +- 0.059 |
| SRBCT | 0.989 +- 0.025 | 1.000 +- 0.001 | 0.978 +- 0.030 | 0.879 +- 0.076 | 0.942 +- 0.045 |
| Lung cancer | 0.969 +- 0.036 | 0.995 +- 0.007 | 0.974 +- 0.027 | 0.753 +- 0.054 | 0.935 +- 0.051 |
| Ranks | 2.33 | 1.00 | 2.67 | 5.00 | 4.00 |
To download the scripts and data sets used to obtain these results click here.