Advances, Systems and Applications
From: Cloud failure prediction based on traditional machine learning and deep learning
Model | Accuracy(%) | Error rate(%) | Precision(%) | Sensitivity(%) | Specificity(%) | F-Score |
---|---|---|---|---|---|---|
Logistic Regression | 69.68 | 30.32 | 71.09 | 79.95 | 55.67 | 0.7526 |
Decision Tree | 89.75 | 10.25 | 85.44 | 98.56 | 78.42 | 0.9153 |
Random Forest | 92.47 | 7.53 | 90.66 | 99.13 | 78.86 | 0.9471 |
Gradient Boosting | 87.81 | 12.19 | 84.81 | 95.92 | 76.86 | 0.9003 |
XGBoost | 89.34 | 10.66 | 85.04 | 98.30 | 77.89 | 0.9119 |
Single Layer LSTM | 87.74 | 12.26 | 83.94 | 96.85 | 75.87 | 0.8994 |
Bi-Layer LSTM | 86.93 | 13.07 | 81.36 | 98.18 | 73.84 | 0.8898 |
Ti-Layer LSTM | 87.54 | 12.46 | 82.90 | 79.53 | 75.27 | 0.8962 |