Research Article
Software Defect Prediction Based on Hybrid Swarm Intelligence and Deep Learning
Table 11
LR1 experimental results.
| | Precision | Recall rate | F-measure | AUC |
| Grid | 0.51 | 0.32 | 0.36 | 0.64 | Grid + self-encoding | 0.61 | 0.39 | 0.47 | 0.68 | Random | 0.50 | 0.30 | 0.31 | 0.63 | Random + self-encoding | 0.60 | 0.35 | 0.43 | 0.66 | PSO | 0.57 | 0.46 | 0.50 | 0.71 | PSO + self-encoding | 0.64 | 0.56 | 0.59 | 0.76 | WPA | 0.61 | 0.53 | 0.56 | 0.74 | WPA + self-encoding | 0.64 | 0.57 | 0.60 | 0.76 | WPA_PSO | 0.62 | 0.58 | 0.59 | 0.77 | WPA_PSO + self-encoding | 0.62 | 0.64 | 0.62 | 0.79 |
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