Binary Classification on Thyroid disease dataset (test)
1AUCXGBoost
Evaluation results
| Method | Links | |
|---|---|---|
| XGBoostmax depth=32025.12 | 1 | |
| Random Forest with 100 treesnumber of trees=100, max depth=32025.12 | 0.98 | |
| Random Forest with 1000 treesnumber of trees=1000, max depth=32025.12 | 0.98 | |
| Soft Decision Treemax depth=32025.12 | 0.98 | |
| SM-SDTmax depth=3, short-term memory=true2025.12 | 0.98 | |
| Decision Treemax depth=32025.12 | 0.96 | |
| Logistic Regression2025.12 | 0.96 |