Table A.4
Effect of our model’s stability by different selections of M and K.
| Different selections of M and K | Precision | Accuracy | Recall | F1 score | MCC | AP | Sum |
|---|---|---|---|---|---|---|---|
| ZTF-NEWm | |||||||
| M=100, K=900 | 96.2±6.0 | 94.9±2.8 | 87.1±11.9 | 90.8±5.5 | 88.0±6.5 | 99.8±0.3 | 556.7±16.1 |
| M=200, K=800 | 96.2±3.4 | 97.4±1.4 | 95.2±5.5 | 95.6±2.5 | 93.9±3.3 | 99.7±0.3 | 578.0±7.8 |
| M=300, K=700 | 98.3±1.0 | 98.4±0.4 | 96.5±1.7 | 97.4±0.7 | 96.3±0.9 | 99.9±0.1 | 586.7±2.3 |
| M=400, K=600 | 97.4±0.7 | 98.5±0.2 | 97.6±1.1 | 97.5±0.2 | 96.4±0.4 | 99.7±0.1 | 587.1±1.3 |
| M=500, K=500 | 97.3±0.9 | 98.5±0.3 | 97.8±0.5 | 97.5±0.5 | 96.5±0.8 | 99.9±0.1 | 587.4±1.5 |
| M=600, K=400 | 97.6±0.8 | 98.5±0.5 | 97.5±1.7 | 97.5±0.8 | 96.5±1.2 | 99.7±0.2 | 587.4±2.4 |
| M=700, K=300 | 97.7±0.9 | 98.5±0.3 | 97.5±0.8 | 97.6±0.5 | 96.5±0.7 | 99.5±0.4 | 587.3±1.6 |
| M=800, K=200 | 97.3±1.1 | 98.5±0.2 | 97.7±1.4 | 97.5±0.4 | 96.4±0.6 | 99.6±0.4 | 587.0±2.0 |
| M=900, K=100 | 97.6±0.4 | 98.6±0.1 | 97.6±0.3 | 97.6±0.2 | 96.6±0.3 | 99.5±0.6 | 587.5±0.8 |
Notes. It can be shown that our algorithm’s results tend to stabilize once M ≥ 400. We employ precision, accuracy, recall, F1 score, Matthews correlation coefficient (MCC), and average precision (AP) as performance measurement indicators. The overall performance measurement is obtained by summing the values of these six indicators (shown in the last column). All results listed are SSLS (R = 3).
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