Table 4 Section identification for the same set of characters groups. The hyperparameters were the same as in Table 3
From: Species determination using AI machine-learning algorithms: Hebeloma as a case study
Testing set | Metrics (/100) | |||||
|---|---|---|---|---|---|---|
Character group | size (n) | Top 1 | Top 3 | Top 5 | MRR | F1m |
CG1 | 790 | 75.2 | 96.5 | 99.1 | 85.6 | 56.3 |
CG2 | 779 | 88.4 | 98.5 | 99.7 | 93.5 | 72.4 |
CG3 | 678 | 79.9 | 97.8 | 99.4 | 88.8 | 67.0 |
CG4 | 685 | 89.8 | 99.1 | 99.9 | 94.5 | 74.9 |
CG5 | 671 | 94.5 | 99.6 | 99.9 | 97.0 | 81.0 |
CG6 | 671 | 94.6 | 99.0 | 99.9 | 96.9 | 80.0 |
CG7 | 671 | 94.9 | 99.3 | 99.9 | 97.2 | 82.8 |
CG8 | 528 | 94.5 | 99.4 | 100.0 | 97.0 | 80.0 |
CG9 | 469 | 94.7 | 99.6 | 99.8 | 97.1 | 82.2 |