Table 4 Comparison of the performance metrics of the XGBoost model, random forest model, support vector machine model, logistic regression model, and K-nearest neighbour algorithm model
From: Construction of the XGBoost model for early lung cancer prediction based on metabolic indices
Algorithm | AUC | Accuracy(%) | Precision | F1 score | Recall |
|---|---|---|---|---|---|
XGBoost | 0.81 | 75.29 | 0.76 | 0.79 | 0.83 |
Random Forest | 0.78 | 72.55 | 0.75 | 0.77 | 0.79 |
KNeighbors | 0.69 | 66.67 | 0.69 | 0.72 | 0.76 |
SVM | 0.77 | 71.37 | 0.74 | 0.76 | 0.78 |