Task A-3 Multi-label classification on CTI-HAL
26.3F1 (Weighted)Label Powerset SVM
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| Label Powerset SVMClassifier=SVM, Strategy=Label Powerset2026.03 | 26.3 | 88.1 | 89.5 | 92.1 | 36.9 | |
| Binary Relevance RFClassifier=Random Forest, Strategy=Binary Relevance2026.03 | 18.3 | 91.6 | 84.2 | 88.5 | 29 | |
| SecureBERT + RFModel=SecureBERT, Classifier=Random Forest2026.03 | 14.3 | 91.4 | 94.7 | 88.3 | 30.8 | |
| NB + OneVsRestClassifier=Naive Bayes, Strategy=OneVsRest2026.03 | 12.2 | 91.1 | 94.7 | 90 | 33.7 | |
| SVM + OneVsRestClassifier=SVM, Strategy=OneVsRest2026.03 | 6.2 | 91 | 94.7 | 84.5 | 26.1 |