Advances, Systems and Applications
Table 4 This table presents the performance results of each predictive model for the job level based on the training dataset, where the model in bold represents the best model
From: Cloud failure prediction based on traditional machine learning and deep learning
Model | Accuracy(%) | Error rate(%) | Precision(%) | Sensitivity(%) | Specificity(%) | F-Score |
|---|---|---|---|---|---|---|
Logistic Regression | 63.11 | 34.66 | 41.44 | 55.65 | 66.30 | 0.4751 |
Decision Tree | 93.43 | 8.08 | 92.19 | 91.56 | 94.70 | 0.9187 |
Random Forest | 93.27 | 7.63 | 91.47 | 91.80 | 94.26 | 0.9163 |
Gradient Boosting | 90.72 | 9.43 | 91.40 | 86.35 | 93.96 | 0.8098 |
XGBoost | 94.49 | 6.27 | 94.46 | 92.08 | 96.19 | 0.9325 |
Single Layer LSTM | 88.83 | 12.27 | 85.75 | 86.42 | 90.44 | 0.8609 |
Bi-Layer LSTM | 89.91 | 11.42 | 86.42 | 88.29 | 90.97 | 0.8734 |
Ti-Layer LSTM | 85.10 | 14.77 | 81.75 | 81.34 | 87.65 | 0.8155 |