Research Article
Software Defect Prediction through Neural Network and Feature Selections
Table 18
Comparison of RBF results with other previous methods before feature selection for PC4 data set.
| Source | Algorithm | F-measure | Accuracy (%) |
| [47] | Naive Bayes | 0.92 | 85.51 | MLP | 0.94 | 89.11 | SVM | 0.94 | 88.45 | RBF | 0.93 | 27.27 |
| [31] | RF | 0.90 | 90.00 | DS | 0.86 | 85.00 | SVM | 0.84 | 81.00 | LR | 0.84 | 82.00 |
| [49] | RBF | 0.25 | 87.40 | KNN | 0.28 | 85.82 | DT | 0.58 | 86.87 |
| This research | RBF | 0.95 | 94.44 |
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