Table 1 Comparative analysis of performance of the 9 algorithms chosen
Algorithms | PrecisionAtRecall (0.8) |
|---|---|
Gradient Boosting Classifier | 0.6827 |
Logistic Regression | 0.6613 |
Random Forest Classifier | 0.6467 |
Extra Trees Classifier | 0.6393 |
Naive Bayes | 0.6160 |
Ada Boost Classifier | 0.5880 |
Light Gradient Boosting Machine | 0.5793 |
K Neighbors Classifier | 0.5027 |
Decision Tree Classifier | 0.3567 |