Table 2.
KluDo’s performance over the test datasets
| LED | MD | MED | RL | |||||
|---|---|---|---|---|---|---|---|---|
| KK | SP | KK | SP | KK | SP | KK | SP | |
| Benchmark_1 | ||||||||
| OL | 89.9 | 91.2 | 90.1 | 90.3 | 89.7 | 90.9 | 88.6 | 89.7 |
| ARI | 92.5 | 93.8 | 92.5 | 92.5 | 92.2 | 93.8 | 92.0 | 92.5 |
| Benchmark_2 | ||||||||
| OL | 77.6 | 79.5 | 76.9 | 77.6 | 78.2 | 79.5 | 74.4 | 74.4 |
| ARI | 85.3 | 85.9 | 85.9 | 85.3 | 85.9 | 85.3 | 84.0 | 82.1 |
| Benchmark_3 | ||||||||
| OL | 80.7 | 83.7 | 80.7 | 82.2 | 81.5 | 83.7 | 77.0 | 79.3 |
| ARI | 87.4 | 88.9 | 87.4 | 88.9 | 87.4 | 88.1 | 85.2 | 85.2 |
| Islam | ||||||||
| OL | 88.0 | 89.3 | 86.7 | 86.7 | 89.3 | 88.0 | 82.7 | 82.7 |
| ARI | 92.0 | 93.3 | 90.7 | 93.3 | 90.7 | 93.3 | 90.7 | 92.0 |
| Jones | ||||||||
| OL | 94.5 | 92.7 | 89.1 | 92.7 | 90.9 | 92.7 | 90.9 | 92.7 |
| ARI | 96.4 | 98.2 | 96.4 | 98.2 | 94.5 | 98.2 | 98.2 | 98.2 |
| ASTRAL40 | ||||||||
| OL | 84.0 | 84.7 | 84.0 | 84.7 | 84.1 | 84.7 | 83.2 | 83.8 |
| ARI | 87.3 | 87.8 | 87.4 | 87.1 | 87.4 | 87.7 | 86.9 | 86.9 |
KluDo’s accuracy for all combinations of the four kernels (LED, MD, MED and RL) and two clustering algorithms (kernel k-means and spectral clustering denoted by KK and SP, respectively) against the datasets Benchmark_1, Benchmark_2, Benchmark_3, Islam, Jones and ASTRAL40. The accuracies are based on the OL and ARI scores with the thresholds of 85% and 50%, respectively. The maximum accuracy in each row is illustrated in bold