| train(Column[], Column[], double, int, int, int, double) |   | 93% | | 92% | 2 | 14 | 1 | 26 | 0 | 1 |
| takeStep(int, int, double[][], double[]) | | 98% | | 95% | 1 | 11 | 1 | 48 | 0 | 1 |
| error(Column[], Column[], int, int) | | 97% | | 64% | 5 | 8 | 0 | 8 | 0 | 1 |
| validatePreconditions(Column[], Column[], int, int, int, double) | | 96% | | 50% | 1 | 2 | 0 | 3 | 0 | 1 |
| getDeltaB(double[][], double[], int, double, double, double, int, double, double, double) | | 100% | | 100% | 0 | 8 | 0 | 22 | 0 | 1 |
| examineExample(int, double[][], double[]) | | 100% | | 100% | 0 | 13 | 0 | 18 | 0 | 1 |
| getRange(double, double, double, double) | | 100% | | 100% | 0 | 4 | 0 | 14 | 0 | 1 |
| findMaxDifference(double, double[]) | | 100% | | 100% | 0 | 5 | 0 | 11 | 0 | 1 |
| learnedFunction(Matrix) | | 100% | | 100% | 0 | 3 | 0 | 6 | 0 | 1 |
| precomputeKernels() | | 100% | | 100% | 0 | 3 | 0 | 5 | 0 | 1 |
| partialError(int, int, double, double[]) | | 100% | | 100% | 0 | 3 | 0 | 3 | 0 | 1 |
| SVM(Kernel, Random) | | 100% | | n/a | 0 | 1 | 0 | 7 | 0 | 1 |
| setTrainingParam(int, double) | | 100% | | 75% | 1 | 4 | 0 | 8 | 0 | 1 |
| simulate(Column) | | 100% | | n/a | 0 | 1 | 0 | 3 | 0 | 1 |
| simulate(Column, Column) | | 100% | | n/a | 0 | 1 | 0 | 2 | 0 | 1 |
| SVM(Kernel) | | 100% | | n/a | 0 | 1 | 0 | 2 | 0 | 1 |
| static {...} | | 100% | | n/a | 0 | 1 | 0 | 1 | 0 | 1 |