Table 2. Relative rank of classifiers.
| Perceptron | kNN | Random Forest | Naive | Logistic | SVM | Bayes Net | C4.5 | Simple CART | Top | |
| Perceptron | - | 35% | 72% | 62% | 70% | 91% | 98% | 93% | 93% | 32% |
| kNN | 65% | - | 78% | 75% | 60% | 88% | 91% | 83% | 79% | 17% |
| Random Forest | 28% | 22% | - | 41% | 32% | 80% | 85% | 78% | 85% | 17% |
| Naive Bayes | 38% | 25% | 59% | - | 60% | 81% | 95% | 88% | 96% | 16% |
| Logistic | 30% | 40% | 68% | 38% | - | 67% | 86% | 72% | 75% | 14% |
| SVM | 7% | 12% | 20% | 19% | 33% | - | 47% | 26% | 37% | 2% |
| Bayes Net | 2% | 9% | 15% | 5% | 14% | 53% | - | 22% | 33% | 1% |
| C4.5 | 6% | 17% | 22% | 12% | 28% | 74% | 78% | - | 80% | 0% |
| Simple CART | 7% | 21% | 15% | 4% | 25% | 63% | 67% | 20% | - | 0% |
Percentage of parameter configurations where the classifier in row 
had an higher accuracy than the classifier in column 
. The last column shows the percentage of configurations in which each respective classifier provided the highest accuracy.