Table 2.
Classification Algorithms | Accuracy | Precision | Recall | F-Measures | F2-Measures |
---|---|---|---|---|---|
Simple Logistic Regression Learning | 97.49% | 97.89% | 95.21% | 96.53% | 95.73% |
K-Nearest Neighbor Classification | 97.49% | 98.48% | 89.70% | 93.88% | 91.32% |
Support Vector Machine | 96.23% | 91.88% | 93.94% | 92.89% | 93.52% |
Random Decision Forest | 94.22% | 93.86% | 82.88% | 88.02% | 84.86% |
Stochastic Gradient Descent Learning | 92.11% | 84.38% | 89.20% | 86.72% | 88.19% |
Decision Tree | 90.45% | 87.14% | 87.00% | 87.06% | 87.02% |
Naïve Bayes Classification | 91.60% | 91.90% | 91.80% | 91.84% | 91.81% |