Research Article
Impact of Parameter Tuning for Optimizing Deep Neural Network Models for Predicting Software Faults
Table 6
Accuracy comparison with different dropout rates.
| | Dropout rate | KC1 | KC3 | PC1 | PC2 |
| | DR (0.1) | 90.89 | 96.00 | 89.00 | 97.10 | | DR (0.2) | 90.00 | 96.00 | 93.34 | 98.19 | | DR (0.3) | 91.60 | 96.21 | 92.00 | 98.19 | | DR (0.4) | 92.00 | 97.00 | 95.22 | 99.00 | | DR (0.5) | 92.00 | 97.00 | 96.00 | 99.00 | | DR (0.6) | 89.66 | 97.00 | 94.45 | 98.11 | | DR (0.7) | 70.23 | 92.90 | 94.45 | 90.00 |
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