Research Article
Surprise Bug Report Prediction Utilizing Optimized Integration with Imbalanced Learning Strategy
Table 5
The performance of seven classification algorithms.
| Projects | Evaluation | NB | J48 | KNN | RT | RF | NBM | SVM |
| Ambari | Precision | 0.273 | 0.178 | 0.268 | 0.389 | 0.412 | 0.303 | Null | Recall | 0.34 | 0.151 | 0.208 | 0.396 | 0.132 | 0.189 | 0 | F-Measure | 0.303 | 0.163 | 0.234 | 0.393 | 0.2 | 0.233 | Null |
| Camel | Precision | 0.457 | 0.271 | 0.357 | 0.49 | 0.482 | 0.392 | Null | Recall | 0.348 | 0.283 | 0.326 | 0.544 | 0.283 | 0.435 | 0 | F-Measure | 0.395 | 0.277 | 0.341 | 0.516 | 0.356 | 0.412 | Null |
| Derby | Precision | 0.333 | 0.278 | 0.182 | 0.095 | 0.333 | 0.5 | Null | Recall | 0.409 | 0.227 | 0.091 | 0.091 | 0.046 | 0.136 | 0 | F-Measure | 0.367 | 0.25 | 0.121 | 0.093 | 0.08 | 0.214 | Null |
| Wicket | Precision | 0.341 | 0.373 | 0.311 | 0.35 | 0.263 | 0.5 | Null | Recall | 0.306 | 0.388 | 0.286 | 0.429 | 0.102 | 0.245 | 0 | F-Measure | 0.323 | 0.38 | 0.298 | 0.385 | 0.147 | 0.329 | Null |
| avgPrecision | 0.351 | 0.275 | 0.28 | 0.331 | 0.372 | 0.424 | Null | avgRecall | 0.351 | 0.262 | 0.228 | 0.365 | 0.141 | 0.251 | 0 | avgF-Measure | 0.347 | 0.268 | 0.249 | 0.347 | 0.196 | 0.297 | Null |
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