Table 5 Average performance of machine learning models across all tumor classes based on AUC, accuracy, F1 score, precision, and recall.
From: Brain tumor detection with real-world predictions in Jordan hospitals
Model | AUC | CA | F1 | Prec | Recall |
|---|---|---|---|---|---|
Tree | 0.873 | 0.81 | 0.81 | 0.81 | 0.81 |
AdaBoost | 0.866 | 0.799 | 0.799 | 0.799 | 0.799 |
kNN | 0.99 | 0.935 | 0.935 | 0.937 | 0.935 |
Neural Network | 0.996 | 0.958 | 0.958 | 0.958 | 0.958 |
Logistic Regression | 0.971 | 0.906 | 0.906 | 0.906 | 0.906 |
Random Forest | 0.972 | 0.879 | 0.879 | 0.878 | 0.879 |
SVM | 0.993 | 0.94 | 0.94 | 0.942 | 0.94 |
