Research Article
Surprise Bug Report Prediction Utilizing Optimized Integration with Imbalanced Learning Strategy
Table 6
The performance of 10 groups of classification algorithms.
| Projects | Evaluation | G1 | G2 | G3 | G4 | G5 | G6 | G7 | G8 | G9 | G10 |
| Ambari | Precision | 0.308 | 0.378 | 0.382 | 0.305 | 0.28 | 0.329 | 0.313 | 0.311 | 0.425 | 0.301 | Recall | 0.83 | 0.698 | 0.491 | 0.868 | 0.698 | 0.509 | 0.887 | 0.793 | 0.585 | 0.83 | F-Measure | 0.449 | 0.49 | 0.43 | 0.451 | 0.4 | 0.4 | 0.463 | 0.447 | 0.492 | 0.442 |
| Camel | Precision | 0.414 | 0.433 | 0.385 | 0.414 | 0.414 | 0.424 | 0.414 | 0.409 | 0.439 | 0.414 | Recall | 1 | 0.63 | 0.326 | 1 | 1 | 0.609 | 1 | 0.978 | 0.63 | 1 | F-Measure | 0.586 | 0.513 | 0.353 | 0.586 | 0.586 | 0.5 | 0.586 | 0.577 | 0.518 | 0.586 |
| Derby | Precision | 0.211 | 0.143 | 0.143 | 0.208 | 0.218 | 0.182 | 0.215 | 0.229 | 0.206 | 0.222 | Recall | 0.826 | 0.304 | 0.217 | 0.87 | 0.826 | 0.348 | 0.87 | 0.826 | 0.304 | 0.87 | F-Measure | 0.336 | 0.194 | 0.172 | 0.336 | 0.346 | 0.239 | 0.345 | 0.359 | 0.246 | 0.354 |
| Wicket | Precision | 0.398 | 0.392 | 0.37 | 0.378 | 0.397 | 0.397 | 0.383 | 0.405 | 0.385 | 0.381 | Recall | 1 | 0.633 | 0.347 | 0.98 | 0.98 | 0.592 | 1 | 1 | 0.51 | 0.98 | F-Measure | 0.57 | 0.484 | 0.358 | 0.546 | 0.565 | 0.475 | 0.554 | 0.577 | 0.439 | 0.549 |
| avgPrecision | 0.333 | 0.336 | 0.32 | 0.326 | 0.328 | 0.333 | 0.331 | 0.339 | 0.364 | 0.33 | avgRecall | 0.914 | 0.566 | 0.345 | 0.929 | 0.876 | 0.514 | 0.939 | 0.899 | 0.508 | 0.92 | avgF-Measure | 0.485 | 0.421 | 0.328 | 0.48 | 0.474 | 0.404 | 0.487 | 0.49 | 0.424 | 0.483 |
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